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aiml - sr backend engineer, data and ml innovation

aiml - sr machine learning engineer, data and ml innovation

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machine learning engineer Jobs in Seattle

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aiml - applied ml engineer, data generation & verification Jobs in Seattle

aiml - sr backend engineer, data and ml innovation Jobs in Seattle

aiml - sr machine learning engineer, data and ml innovation Jobs in Seattle

aiml applied ml engineer data generation verification

Lightning AI

<div><div><h2 class="jobSectionHeader"><b>Who </b><b>We Are</b></h2>
<p>
Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems&mdash;designed to take ideas from research to production with less friction.</p>
<p>
Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in.</p>
<p>
We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute.</p>
<h2 class="jobSectionHeader"><b>
The Way We Work</b></h2>
<p>
The people who thrive here are builders who move fast, communicate openly, take ownership, and continuously improve themselves, their teams, and our company. Here's what that looks like in practice:</p>
<ul>
<li><b>Move with Urgency:</b> We move quickly, make thoughtful decisions, and keep momentum. We value action over perfection and learn by shipping.</li>
<li><b>Take Ownership:</b> We own outcomes, not just our individual work. We make decisions that move the company forward and follow through.</li>
<li><b>Communicate Openly:</b> We communicate directly, seek to understand, and create clarity for others. Honest conversations help us move faster together.</li>
<li><b>Build Great Teams:</b> We lead by example, empower others, and create healthy teams where people can do their best work.</li>
<li><b>Raise the Bar:</b> We're always improving ourselves. We learn from feedback, consistently challenge ourselves to grow, and focus on the work that matters most.</li>
<li><b>Think Long-Term:</b> We design for what's next. We create scalable systems, simplify complexity, and use AI and automation to amplify our impact.</li>
</ul>
</div><div></div><h2 class="jobSectionHeader"><b>What We're Looking For</b></h2>
<p>
Lightning AI is looking to hire an <b>AI</b> <b>Platform Support Engineer </b>to join our US Customer Experience team, supporting ML engineers running large-scale training and inference workloads across cloud infrastructure, Kubernetes, and GPU platforms in production environments.</p>
<p>
This role sits at the intersection of ML systems, cloud infrastructure, Kubernetes, and customers. You'll support engineers training models, deploying inference systems, and scaling GPU workloads in production.You are not a ticket router or traditional support engineer. You are a technical partner to ML teams - helping diagnose failures, improve reliability, and guide customers through complex distributed systems problems.</p>
<p>
The problems range from Kubernetes scheduling and GPU orchestration to distributed PyTorch failures, inference latency, networking bottlenecks, storage performance, and platform reliability. You'll gain exposure to a wide variety of real world AI workloads across industries and help shape the infrastructure powering the next generation of ML applications.</p>
<p><i>
This role is hybrid out of our Seattle, San Francisco, or New York office hubs, with an in-office requirement of at least 2 days per week and occasional team and company offsites. The role follows a Monday&ndash;Friday schedule, with working hours from 8:00 AM to 5:00 PM PST. We are not able to provide visa sponsorship for this role at this time.</i></p><h2 class="jobSectionHeader"><br>
<b>
What You'll Do</b></h2>
<p><b>
Work Directly With ML Engineers</b></p>
<ul>
<li>Partner directly with customer engineering teams running training and inference workloads in production</li>
<li>Help customers diagnose and resolve complex distributed systems and ML infrastructure issues</li>
<li>Act as a technical advisor during high impact incidents and platform degradation events</li>
<li>Translate infrastructure level issues into actionable guidance for ML engineers</li>
<li>Build credibility with customers through strong technical reasoning and clear communication</li>
</ul>
<p><b>Debug ML Infrastructure &amp; Distributed Workloads</b></p>
<ul>
<li>Investigate failures involving distributed training, Kubernetes orchestration, GPU allocation, networking, and storage systems</li>
<li>Troubleshoot PyTorch, CUDA, NCCL, and inference serving related issues</li>
<li>Analyze logs, metrics, traces, and system behavior to isolate root causes</li>
<li>Debug containerized workloads running across Kubernetes and bare metal GPU environments</li>
<li>Support customers scaling workloads across multi node GPU systems</li>
<li>Diagnose performance bottlenecks involving compute, memory, networking, or storage</li>
</ul>
<p><b>Improve Reliability &amp; Platform Operations</b></p>
<ul>
<li>Identify recurring patterns across customer issues and drive long term reliability improvements</li>
<li>Contribute to post incident reviews and operational improvements</li>
<li>Build internal tooling, automation, documentation, and runbooks</li>
<li>Partner closely with infrastructure, networking, and platform engineering teams</li>
<li>Help improve observability, operational visibility, and troubleshooting workflows</li>
<li>Improve the customer experience through better processes and technical guidance</li>
</ul>
<p><b>What This Role Is Not</b></p>
<p>
To set clear expectations:</p>
<ul>
<li>This is not a traditional help desk or ticket routing support role</li>
<li>This is not purely customer success or account management</li>
<li>This is not a backend engineering role</li>
<li>This is not a passive escalation position</li>
</ul>
<p>This role is for engineers who enjoy solving difficult technical problems while working closely with other engineers.</p><br>
<p></p>
<h2 class="jobSectionHeader"><b>
What You'll Need</b></h2>
<h3 class="jobSectionHeader"><b>Required Qualifications</b></h3>
<h4 class="jobSectionHeader"><b>Infrastructure &amp; Systems</b></h4>
<ul><li>Strong software engineering and systems troubleshooting background</li>
<li>Experience with Kubernetes and containerized environments</li>
<li>Linux systems knowledge, including networking, storage, process management, and performance tuning</li>
<li>Experience with cloud infrastructure and distributed systems</li>
<li>Experience with observability and debugging tools such as Prometheus, Grafana, or OpenTelemetry</li>
</ul><h4 class="jobSectionHeader"><b>ML Infrastructure Experience</b></h4>
<ul><li>Hands on experience operating machine learning workloads in production or research environments</li>
<li>Experience with distributed ML systems and tooling such as PyTorch, CUDA, or NCCL</li>
<li>Familiarity with GPU infrastructure and orchestration</li>
<li>Experience troubleshooting performance, reliability, or scaling issues in ML infrastructure</li>
<li>Understanding of the operational challenges involved in running ML systems at scale</li>
</ul><h4 class="jobSectionHeader"><b>Collaboration</b></h4>
<ul><li>Strong communication skills and ability to work directly with highly technical customers and engineering teams</li>
<li>Comfortable operating in fast moving, highly ambiguous environments</li>
<li>Enjoys solving complex technical problems collaboratively</li>
</ul><h3 class="jobSectionHeader"><b>Ideal Experience</b></h3>
<ul><li>Experience with large scale model training or distributed inference systems</li>
<li>Familiarity with Ray, Kubeflow, Slurm, or similar distributed scheduling platforms</li>
<li>Experience with InfiniBand, RDMA, or high-performance networking</li>
<li>Experience operating bare metal infrastructure</li>
<li>Familiarity with storage systems commonly used in ML environments</li>
<li>Experience working at an AI infrastructure, cloud, MLOps, or developer tooling company</li>
<li>Contributions to platform engineering, developer infrastructure, or operational tooling projects</li>
<li>Experience writing automation, tooling, or scripts in Python or similar languages</li>
</ul><div><h2 class="jobSectionHeader"><b>Benefits and Perks</b></h2>
<p>
We offer a comprehensive and competitive benefits package designed to support our employees' health, well-being, and long-term success:</p>
<ul>
<li><b>Comprehensive Health Coverage:</b> Medical, dental, and vision coverage for employees and eligible dependents.</li>
<li><b>Meaningful Equity:</b> RSUs that give employees a stake in the company's long-term success.</li>
<li><b>Retirement Savings:</b> 401(k) matching (U.S.) and pension contributions (U.K.).</li>
<li><b>Flexible Time Off:</b> Unlimited PTO, company holidays, and floating holidays to support work-life balance.</li>
<li><b>Company-Wide Winter Break:</b> Two weeks of company closure each winter to disconnect and recharge.</li>
<li><b>Paid Parental &amp; Family Leave:</b> Paid leave to support you and your family through life's important moments.</li>
<li><b>Professional Development:</b> Annual learning and development allowance to support your professional growth.</li>
<li><b>Wellness Benefits:</b> Wellness and work-from-home stipends to support your physical and mental well-being.</li>
<li><b>Sabbatical Program:</b> Four weeks of paid sabbatical leave after four years of service.</li>
<li><b>Flexible Work:</b> Flexible schedules and a hybrid work model for our office-based teams.</li>
<li><b>In-Office Meals:</b> Complimentary meals at our office hubs.</li>
</ul>
<p>Benefits may vary by location, team, and role.</p><br>
<p></p>
<p><i>
At Lightning AI, we are committed to fostering an inclusive and diverse workplace. We believe that diverse teams drive innovation and create better products. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic. We are dedicated to building a culture where everyone can thrive and contribute to their fullest potential.</i></p></div></div>

AI Platform Support Engineer (US)

Amazon.com

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
Here's the job description with causal ML woven in:<br>
<br>
We are looking for a talented, organized, and customer-focused applied researcher to join our Pricing Optimization science group, with a charter to measure, refine, and launch customer-obsessed improvements to our algorithmic pricing and promotion models across all products listed on Amazon.<br>
<br>
This role requires an individual with exceptional machine learning modeling and architecture expertise &mdash; particularly in deep learning, neural networks, and transformer-based architectures applied to price prediction and forecasting problems. Equally important is deep expertise in causal machine learning &mdash; including causal inference, treatment-effect estimation, and experimentation methods (e.g., uplift modeling, double/debiased machine learning, instrumental variables, and A/B and quasi-experimental design) &mdash; to isolate the true impact of pricing and promotion decisions on customer behavior and business outcomes. The ideal candidate brings a strong foundation in applied statistics and probabilistic modeling, excellent cross-functional collaboration skills, business acumen, and an entrepreneurial spirit.<br>
<br>
We are looking for an experienced innovator who is a self-starter, comfortable with ambiguity, demonstrates strong attention to detail, and has the ability to work in a fast-paced and ever-changing environment.<br>
<br>
Key job responsibilities<br>
See the big picture. Understand and influence the long-term vision for Amazon's science-based competitive, perception-preserving pricing techniques. Develop and advance price prediction models leveraging deep learning frameworks, transformer architectures, and advanced statistical methods to drive pricing accuracy at scale.<br>
<br>
Build strong collaborations. Partner with product, engineering, and science teams within Pricing &amp; Promotions to deploy machine learning price estimation and error correction solutions at Amazon scale. Design and implement neural network-based architectures &mdash; including sequence models and transformers &mdash; for large-scale price prediction and optimization.<br>
<br>
Stay informed. Establish mechanisms to stay up to date on the latest scientific advancements in deep learning, transformer architectures, applied statistics, neural network design, probabilistic forecasting, and multi-objective optimization techniques. Identify opportunities to apply them to relevant Pricing &amp; Promotions business problems.<br>
<br>
Keep innovating for our customers. Foster an environment that promotes rapid experimentation, continuous learning, and incremental value delivery. Leverage statistical rigor and modern deep learning approaches to validate hypotheses and drive measurable pricing improvements.<br>
<br>
Successfully execute &amp; deliver. Apply your exceptional technical machine learning expertise &mdash; including deep neural networks, attention-based models, and applied statistical analysis &mdash; to incrementally move the needle on some of our hardest pricing problems.<br>
<br>
A day in the life<br>
We are hiring a Sr. Applied Scientist to drive our pricing optimization initiatives. We drive cross-domain and cross-system improvements through:<br>
<br>
<ul><li>shape and extend our RL optimization platform - a pricing centric tool that automates the optimization of various system parameters and price inputs.</li><li>Error detection and price quality guardrails at scale.</li><li>Identifying opportunities to optimally price across systems and contexts (marketplaces, request types, event periods)</li></ul><br>
Price is a highly relevant input into Stores architectures; this role creates the opportunity to drive extremely large impact (measured in Bs not Ms), but demands careful thought and clear communication.<br>
<br>
About the team<br>
The Pricing Optimization science group builds and refines Amazon's algorithmic pricing and promotion models at scale. Our team combines expertise in deep learning, transformer architectures, applied statistics, and probabilistic forecasting to develop price prediction systems that directly impact the customer experience. The team also brings hands-on experience with causal modeling and inference &mdash; including uplift modeling and treatment effect estimation &mdash; to rigorously measure the impact of pricing decisions on customer behavior and business outcomes. We partner closely with product, engineering, and business teams to take solutions from research through production deployment.</div><h2 class="jobSectionHeader"><b><br>
BASIC QUALIFICATIONS</b></h2><ul><li>4+ years of applied research experience</li><li>3+ years of building machine learning models for business application experience</li><li>PhD, or Master's degree and 6+ years of applied research experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience with neural deep learning methods and machine learning</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.</li><li>Experience with large scale distributed systems such as Hadoop, Spark etc.</li></ul><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.<p><br>
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.</p><br>
USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually</div><p></p>

Sr. Applied Scientist, Pricing Science

Amazon Web Services

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><p>
AI is not just changing what software can do; it is fundamentally changing how software is built. We are building the next generation of developer tooling: an AI-native tool that redefines the software engineering workflow from the ground up. Our product sits at the center of a developer's day, and we are obsessed with making that experience fast, delightful, and powerful.
<br>
<br>
We are looking for engineers who are passionate about building exceptional user-facing client software. If you care deeply about UI responsiveness, interaction design, and the quality of tools engineers use to build software, this team is for you.
<br>
<br>
You will work alongside exceptional senior engineering talent solving hard problems at the frontier of AI and developer tooling. You'll have opportunities to work with and learn from best-in-industry senior engineering talent. In addition to the technical challenges provided by the innovative use cases that we are working on, you will also learn how to build a product that meets AWS's high bar for availability, scalability, and security.
<br>
<br>
You'll have a direct line to our customers' experience and a direct means of improving it. On a daily basis, you'll work with teammates to review each other's code, mentor and be mentored. You'll have an opportunity to lead from day one, from leading projects, to driving technical processes, to teaching and learning from your teammates. You will have real ownership, from setting technical direction to shipping features that developers notice and love.
<br>
<br>
Key job responsibilities<br>
Own the end-to-end delivery of high-impact, user-facing features built with TypeScript and React, from writing the technical spec to shipping to customers
<br>
<br>
Drive technical direction for client-side architecture and establish patterns that raise the bar for quality across the team
<br>
<br>
Work closely with designers and product managers to ensure every feature meets a high bar for developer UX and interaction quality
<br>
<br>
Build and use AI agents to accelerate your own development workflow
<br>
<br>
Exercise high judgment about when to guide, override, or take control from AI agents &mdash; knowing when to trust automation and when the situation demands your direct involvement
<br>
<br>
Mentor and guide less tenured engineers, helping them navigate technical challenges, grow their skills, and advance their careers
<br>
<br>
Work with Product and Design to deeply understand customer workflows and build backward from their needs, maintaining Amazon's commitment to starting from the customer
<br>
<br>
A day in the life<br>
Use AI agents to write code and move fast, and direct code review agents to help the team catch issues before they ship
<br>
<br>
Conduct design and UX reviews with your PM and designer to ensure every feature meets a high bar for developer experience
<br>
<br>
Take full ownership of a feature set actively used by customers, deliver high-impact features end to end, from the initial spec to the moment they ship, and take pride in building software that genuinely delights the developers who use it every day.
<br>
<br>
Participate in the team's Weekly Operations Review and understand the key metrics that drive our product
<br>
<br>
Work with your manager to understand how to grow your career at AWS and how to build a career growth plan
<br>
<br>
Become an active participant in all stages of our software development cycle, including roadmap planning and product review meetings
<br>
<br>
Work with other engineers to improve our operational effectiveness by designing new systems and making our current ones more effective
<br>
<br>
Help onboard new engineers and guide them in their first weeks at AWS
<br>
<br>
Hold a high bar for user experience in every feature you ship: obsess over every interaction, every millisecond of latency, and choose the path that serves users best even when it is harder to build
<br>
<br>
Continuously measure, monitor, and improve client-side performance across all supported operating systems
<br>
<br>
About the team<br>
We are a team of engineers who believe the way software is built is about to change permanently, and we are the ones defining that change. We are building an AI-native developer environment that sits at the intersection of cutting-edge AI and the craft of software engineering. Our team is obsessed with the developer experience: we care about performance, interaction design, and the small details that make a tool feel fast and effortless. We dogfood our own product every day, which means every improvement we ship makes us better engineers too. If you want to build the tools that shape how the next generation of software is written, this is the team for you.
<br>
<br>
Agentic AI drives innovation at the forefront of artificial intelligence, enabling customers to transform their businesses through cutting-edge AI solutions. We build and deliver the foundational AI services that power the future of cloud computing, helping organizations harness the potential of AI to solve their most complex challenges. Join our dynamic team of AI/ML practitioners, applied scientists, software engineers, and solution architects who work backwards from customer needs to create groundbreaking technologies. If you're passionate about shaping the future of AI while making a meaningful impact for customers worldwide, we want to hear from you.
</p><h2 class="jobSectionHeader"><b>BASIC QUALIFICATIONS</b></h2><ul><li>2+ years of non-internship professional front end, web or mobile software development using JavaScript, HTML and CSS experience</li><li>1+ years of computer science fundamentals (object-oriented design, data structures, algorithm design, problem solving and complexity analysis) experience</li><li>Experience using JavaScript frameworks such as angular and react</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>1+ years of agile software development methodology experience</li><li>Experience with common front-end technologies such as HTML, CSS, JS, TypeScript, and Node</li></ul><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.<p><br>
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.</p><br>
USA, WA, Seattle - 143,700.00 - 194,400.00 USD annually</div><p></p>

Front-End Engineer, Kiro

Whatnot

<div>
 <strong>
  <strong>
   🚀 Join the Future of Commerce with Whatnot!
   <br/>
   <br/>
  </strong>
 </strong>
 Whatnot is the largest live shopping platform in North America and Europe to buy, sell, and discover the things you love. Whether it's trading cards, fashion, electronics, or live plants, our sellers are building real businesses across hundreds of categories. We're building live commerce at a scale that's never been done in the West, and there's no playbook to copy. The people here are shaping how an entirely new industry develops.
 <br/>
 <br/>
 As a remote co-located team, we're inspired by our values and anchored in hubs across the US, UK, Ireland, Poland, Germany, and Australia. We move fast, stay close to our users, and focus on the work that drives the most impact.
 <br/>
 <br/>
 We're one of the fastest growing marketplaces and were recently named the #1 Best Startup Employer in America by Forbes. Check out the latest Whatnot updates on our news and engineering blogs and join us as we enable anyone to turn their passion into a business and bring people together through commerce.
 <br/>
 <br/>
 <strong>
  💻 Role
  <br/>
  <br/>
 </strong>
 Data is crucial to Whatnot&rsquo;s mission to bring people together through commerce.
 <br/>
 <br/>
 As our newest
 <strong>
  Data Engineer
 </strong>
 , you&rsquo;ll build and scale the systems that power data-driven decisions across the company. You&rsquo;ll work directly with stakeholders across the business &ndash; such as product, sales, marketing, finance, and trust teams &ndash; to design reliable data architectures, ship resilient pipelines, and create the foundational data products that power Whatnot&rsquo;s internal and external growth.
 <br/>
 <br/>
 <strong>
  On Any Given Day, You Will
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Own data architecture end-to-end. Define how we capture, model, and serve critical business data&mdash;then implement it in production. You&rsquo;ll make architectural decisions around storage formats, compute patterns, and SLAs that balance cost, scalability, and consistency.
  </li>
  <li>
   Build mission-critical pipelines. Develop and operate streaming and batch data workflows that process high-volume events across multiple domains&mdash;user activity, transactions, experimentation, marketing performance, and operational telemetry&mdash;with tight guarantees for latency, completeness, and accuracy.
  </li>
  <li>
   Design and implement canonical models. Create domain-oriented data models that serve as the source of truth for analytics, ML, and real-time applications. Establish and enforce modeling standards, ownership boundaries, and data contracts across teams.
  </li>
  <li>
   Enforce data quality at scale. Build tests, lineage, monitoring, and reconciliation systems that make every dataset observable and every anomaly actionable.
  </li>
  <li>
   Automate operational workflows. Partner with business systems and platform teams to eliminate manual data handoffs and reconcile data across services, warehouses, and external systems.
  </li>
  <li>
   Enable insights and experimentation. Support analytics, ML, and product engineering teams by exposing high-quality, low-latency data through semantic layers, APIs, and real-time query systems.
   <br/>
   <br/>
  </li>
 </ul>
 Due to the cross-functional nature of this role, candidates will be matched to multiple teams based on need and experience, including product, analytics, or data platforms teams.
 <br/>
 <br/>
 <strong>
  👋 You
  <br/>
  <br/>
 </strong>
 People who do well at Whatnot tend to be comfortable figuring things out as they go, biased toward action, and genuinely curious about what they're building. They care more about outcomes than credit and stay close to the product and the people using it.
 <br/>
 <br/>
 <ul>
  <li>
   Have 3+ years of experience as a data or software engineer building data warehouses, distributed data systems, or event-driven architectures.
  </li>
  <li>
   Can design and implement data models using dimensional, Data Vault, or ledger-style techniques that support analytical and transactional workloads.
  </li>
  <li>
   Have deep hands-on expertise with modern data tooling across ingestion (e.g., Kafka, Debezium), transformation (dbt, Spark, Flink), orchestration (Dagster, Airflow), and observability (Monte Carlo, Great Expectations).
  </li>
  <li>
   Have operated cloud data warehouses such as Snowflake, BigQuery, or Redshift, including schema design, cost optimization, and workload tuning.
  </li>
  <li>
   Are comfortable writing production-grade code in Python or SQL languages, and integrating with CI/CD and infrastructure-as-code workflows.
  </li>
  <li>
   Enjoy partnering across disciplines&mdash;engineering, product, analytics&mdash;to translate messy business requirements into elegant data systems.
  </li>
  <li>
   Thrive as a self-starter in a fast-moving environment, owning both the technical design and the operational outcomes of your work.
   <br/>
   <br/>
  </li>
 </ul>
 If designing the data backbone that powers Whatnot&rsquo;s growth, insights, and product innovation excites you, we&rsquo;d love to meet you.
 <br/>
 <br/>
 <strong>
  We offer flexibility to work from home or from one of our global office hubs, and we value in-person time for planning, problem-solving, and connection. Team members in this role must live within commuting distance of our New York, Seattle, Los Angeles, and San Francisco hubs.
  <br/>
  <br/>
 </strong>
 <strong>
  💰Compensation
  <br/>
  <br/>
 </strong>
 <strong>
  For Full-Time (Salary)
  <br/>
  <br/>
 </strong>
 <strong>
  US based applicants:
 </strong>
 $180,000/year to $260,000/year + benefits + equity.
 <br/>
 <br/>
 The salary range may be inclusive of several levels that would be applicable to the position. Final salary will be based on a number of factors including, level, relevant prior experience, skills, and expertise. This range is only inclusive of base salary, not benefits (more details below) or equity.
 <br/>
 <br/>
 <strong>
  🎁 Benefits
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Generous Holiday and Time off Policy
  </li>
  <li>
   Health Insurance options including Medical, Dental, Vision
  </li>
  <li>
   Work From Home Support
  </li>
  <ul>
   <li>
    Home office setup allowance
   </li>
   <li>
    Monthly allowance for cell phone and internet
   </li>
  </ul>
  <li>
   Care benefits
  </li>
  <ul>
   <li>
    Monthly allowance for wellness
   </li>
   <li>
    Annual allowance towards Childcare
   </li>
   <li>
    Lifetime benefit for family planning, such as adoption or fertility expenses
   </li>
  </ul>
  <li>
   Retirement; 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary) and Pension plans internationally
  </li>
  <li>
   Monthly allowance to dogfood the app
  </li>
  <ul>
   <li>
    All Whatnauts are expected to develop a deep understanding of our product. We're passionate about building the best user experience, and all employees are expected to use Whatnot as both a buyer and a seller as part of their job (our dogfooding budget makes this fun and easy!).
   </li>
  </ul>
  <li>
   Parental Leave
  </li>
  <ul>
   <li>
    16 weeks of paid parental leave + one month gradual return to work *company leave allowances run concurrently with country leave requirements which take precedence.
   </li>
  </ul>
 </ul>
 <strong>
  <strong>
   💛 EOE
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   <br/>
  </strong>
 </strong>
 Whatnot is proud to be an Equal Opportunity Employer. We value diversity, and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, parental status, disability status, or any other status protected by local law. We believe that our work is better and our company culture is improved when we encourage, support, and respect the different skills and experiences represented within our workforce.
 <br/>
 <br/>
 Compensation Range: $180K - $260K
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</div>


Data Engineer

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
Do you want to join an innovative team of scientists and engineers who use terabytes of data and create state-of-the-art Generative AI algorithms to push the boundaries of AI creativity? We are building foundational behavioral models for Amazon Stores using Generative AI, LLMs and Large Model training techniques that fuses general world knowledge, customer shopping behavior and Amazon e-commerce domain knowledge. We are looking for scientists who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry using intelligent and transformative AI applications. Working closely with cross-functional teams, you will be an essential part of every stage of AI development, from ideation and design to rigorous testing and successful deployment, ensuring our AI projects drive innovation and provide value for our customers. If you&rsquo;re fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey!<br>
<br>
Key job responsibilities<br>
In this role you will leverage your background and expertise to lead developing foundational behavioral model for Amazon Stores using Generative AI, LLM and Large Model training techniques. On a day-to-day basis, you will:<br>
<ul><li>Research and implement new algorithms and architectures for generative AI applications.</li><li>Optimize model performance and scalability for inference and deployment.</li><li>Collaborate with other talented applied scientists and engineers to gather and preprocess large datasets and develop an improved training infrastructure that accelerates innovation.</li><li>Experiment with SOTA methods to improve generative AI model quality.</li><li>Provide technical expertise and guidance to support the integration of generative AI solutions into various products and services.</li></ul></div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience</li><li>2+ years of building models for business application experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing</li><li>Experience in patents or publications at top-tier peer-reviewed conferences or journals</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Strong understanding of machine learning, deep learning, and generative AI principles and algorithms.</li><li>Proficiency with modeling and large-scale data processing tools such as Pytorch, scikit-learn, Spark MLLib, PySpark, MxNet, Tensorflow, numpy, scipy etc.</li><li>Ability to work with large datasets and knowledge of data preprocessing techniques such as Hadoop, Spark etc..</li><li>Familiarity with natural language processing (NLP) and computer vision for generative AI applications.</li><li>Strong problem-solving and critical thinking skills and excellent communication and teamwork abilities to collaborate with cross-functional teams.</li><li>Ability to stay updated with the latest advancements in generative AI and adapt to new techniques and methodologies.</li></ul><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.<br>
<br>
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.<p><br>
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.</p><br>
USA, CA, San Diego - 142,800.00 - 193,200.00 USD annually<br>
USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually</div><p></p>

Applied Scientist (GenAI/LLM), Sandstone

SoFi

<div><div><p><b>Employee Applicant Privacy Notice</b></p>
<p><b>
Who we are:</b></p>
<div>
<p>Shape a brighter financial future with us.</p>
<p>
Together with our members, we're changing the way people think about and interact with personal finance.</p>
<p>
We're a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we're at the forefront. We're proud to come to work every day knowing that what we do has a direct impact on people's lives, with our core values guiding us every step of the way. <b>Join us to invest in yourself, your career, and the financial world.</b></p>
</div></div><p><b>
The role</b></p><p><br>
We are seeking a Staff Vulnerability Management Engineer to lead the most complex technical work in SoFi's Vulnerability Management program. You will design and build scalable systems that identify, enrich, prioritize, route, and track vulnerabilities across applications, cloud and infrastructure, containers, software supply chains, and specialized hardware or firmware surfaces. This is a hands-on engineering role with broad technical influence: you will write production code, make architecture decisions, establish vulnerability management standards, and improve how teams understand and reduce vulnerability risk.</p><p><br>
You will partner with Engineering, Infrastructure, SRE, Compliance, Legal, and business stakeholders to accelerate remediation while protecting engineering velocity and customer trust. You will also serve as a senior technical responder for embargoed disclosures and zero-day events, lead root-cause analysis for high-impact vulnerability incidents, and mentor engineers. The ideal candidate combines deep vulnerability management expertise with strong software engineering judgment, systems thinking, and a bias for durable, measurable outcomes.</p><p><br>
<b>
What you'll do</b></p>
<ul>
<li> Lead high-complexity vulnerability management initiatives and make architecture decisions for assigned program areas, from detection and assessment through ticket routing, remediation, exception handling, and closure validation.</li>
<li>Design, build, and productionize scalable triage and prioritization automation, including scanner and asset integrations, enrichment pipelines, decision logic, deduplication, ownership resolution, service-level tracking, observability, and failure recovery.</li>
<li>Develop risk-based prioritization models that combine CVSS, EPSS, CISA Known Exploited Vulnerabilities, threat intelligence, asset criticality, exposure, compensating controls, business context, and compliance obligations.</li>
<li>Engineer and improve vulnerability workflows across application security, cloud and infrastructure, containers and Kubernetes, open-source dependencies, secrets, software supply chain, and hardware-adjacent surfaces such as GPU, DPU/BlueField, BMC, and firmware.</li>
<li>Own or materially advance software supply chain capabilities, including SBOM inventory, dependency visibility, SLSA-aligned controls, and integration of SAST, SCA, secret scanning, and container scanning into CI/CD.</li>
<li>Act as a senior technical responder for critical vulnerabilities, embargoed disclosures, and zero-day events; coordinate technical assessment, containment, mitigation, patch deployment, validation, and executive communication with service owners and incident response teams.</li>
<li>Partner directly with development and platform teams to define practical remediation paths and, when appropriate, review or contribute secure changes in Python, Go, JavaScript/TypeScript, or infrastructure code.</li>
<li>Define technical standards for vulnerability severity, remediation service levels, exceptions, evidence, and closure criteria; ensure workflows support audit-ready reporting for applicable regulatory and compliance frameworks.</li>
<li>Produce actionable metrics, dashboards, and risk insights for technical and executive audiences, with clear accountability, trend analysis, compliance posture, and execution risks.</li>
<li>Lead root-cause analysis for high-impact vulnerability incidents and convert lessons learned into durable improvements to tooling, architecture, controls, and operating practices.</li>
<li>Evaluate and responsibly apply AI/ML and LLM-assisted techniques to security triage and decision support, with human-in-the-loop validation, measurable quality controls, and safe failure modes.</li>
<li>Build AI-assisted remediation workflows that partner with engineering teams to proactively identify, validate, and apply security patches, with appropriate testing, human oversight, rollback mechanisms, and measurable risk reduction.</li>
<li>Communicate complex security tradeoffs and program risks clearly to stakeholders across Engineering, Product, Operations, Legal, Compliance, and executive leadership.</li></ul><br>
<p><br>
<b>What you'll need</b></p>
<ul>
<li>Bachelor's degree in Computer Science, Cybersecurity, Engineering, or a related field, or equivalent practical experience.</li>
<li>Deep expertise in vulnerability management, security engineering, and modern infrastructure, including cloud, containers, and distributed systems.</li>
<li>Strong programming or scripting skills in Python, Go, Java, or similar languages, with experience building automation at scale.</li>
<li>Deep knowledge of vulnerability management methods and standards, including CVSS, EPSS, CISA KEV, threat intelligence integration, asset and exposure context, remediation SLAs, exception governance, and risk-based prioritization.</li>
<li>Hands-on experience with modern vulnerability and application security tooling such as Wiz, Semgrep, Snyk, Socket, Rapid7, Tenable, Checkmarx, or equivalent platforms, plus experience tuning SAST, SCA, secret scanning, container, or cloud findings.</li>
<li>Experience designing end-to-end workflows that integrate scanners, asset inventories or CMDBs, ticketing systems, CI/CD platforms, data stores, dashboards, and alerting systems.</li>
<li>Working knowledge of cloud-native and software supply chain environments, including AWS, GCP, or Azure; Kubernetes and containers; build systems and package managers; SBOMs; and Infrastructure as Code.</li>
<li>Demonstrated ability to lead cross-functional technical initiatives, influence without direct authority, make sound decisions amid ambiguity, and drive work from concept through production operation and measurable outcomes.</li>
<li>Experience mentoring senior and developing engineers and raising engineering quality through design reviews, code reviews, standards, and incident leadership.</li>
<li>Strong written and verbal communication, business judgment, and the ability to explain how security choices affect engineering velocity, regulatory obligations, customer trust, and business risk.</li></ul><br>
<p><br>
<b>Nice to have</b></p>
<ul>
<li>Experience managing security partnerships with hardware or software vendors, including embargoed disclosures, coordinated vulnerability disclosure, and pre-release remediation collaboration.</li>
<li>Production experience with security orchestration platforms such as Tines and serverless frameworks such as AWS Lambda or Google Cloud Functions.</li>
<li>Experience scaling vulnerability management in a high-growth, cloud-native environment or operating within FedRAMP, PCI DSS, SOC 2, ISO 27001, NIST, or comparable regulated environments.</li>
</ul><div><div><b>Compensation and Benefits</b></div>
<div>The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidate's experience, skills, and location.</div>
<div></div>
<div>To view all of our comprehensive and competitive benefits, visit our <b>Benefits at SoFi</b><b> </b>page!</div>
<h5 class="jobSectionHeader">SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identity, gender expression, national origin, ancestry, age (40 or over), physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law.</h5>
<h5 class="jobSectionHeader">The Company hires the best qualified candidate for the job, without regard to protected characteristics.</h5>
<h5 class="jobSectionHeader">Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.</h5>
<h5 class="jobSectionHeader">New York applicants: Notice of Employee Rights</h5>
<h5 class="jobSectionHeader">SoFi is committed to an inclusive culture. As part of this commitment, SoFi offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email <b>accommodations@sofi.com.</b></h5>
<h5 class="jobSectionHeader">Due to insurance coverage issues, we are unable to accommodate remote work from Hawaii or Alaska at this time.</h5>
<div><b>Internal Employees</b></div>
<div>If you are a current employee, do not apply here - please navigate to our Internal Job Board in Greenhouse to apply to our open roles.</div></div></div>

Staff Vulnerability Management Engineer

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><p>
At AWS Cloud &amp; AI Innovation team, our mission is to accelerate customer adoption of AI and maximize the value they get from this technology.
<br>
<br>
As Applied Scientist on our team, your focus will be on solving the most complex problems that prevent our customers from successfully adoption AI at scale. You will research new methods for overcoming obstacles that are beyond engineering solutions. These include advanced methods for agent grounding and evals, novel methods for multi-agent orchestration and semantic data layer, and innovative approaches to optimizing customer token costs, just to name a few.
<br>
<br>
A successful candidate will have a strong machine learning background, a deep understanding of the AI stack, and a desire to push the envelope in applying AI to the most difficult practical problems preventing adoption at scale and in business-critical situations.<br>
<br>
As a senior member of the team, you will own ambiguous, high-impact research problems end-to-end &mdash; from defining the scientific direction to conducting the research, to packaging it into a reusable solution that the rest of the team can apply in customer-facing engagements.
<br>
<br>
As an Applied Scientist, you will leverage your technical expertise to set the research agenda for how we measure conversational quality, mentor engineers and architects, and partner across science, engineering, and business teams. You will analyze and understand customer experiences and develop novel approaches to solving complex problems in applied AI.</p><h2 class="jobSectionHeader"><b><br>
BASIC QUALIFICATIONS</b></h2><ul><li>3+ years of building machine learning models for business application experience</li><li>PhD, or Master's degree and 6+ years of applied research experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience with neural deep learning methods and machine learning</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.</li><li>Experience with large scale distributed systems such as Hadoop, Spark etc.</li></ul><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.<p><br>
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.</p><br>
USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually</div><p></p>

Sr. Applied Scientist, CAIT

Explore 57+ Aiml applied ml engineer data generation verification in Seattle this August. Find roles across top companies and apply now to boost your career.