aiml - applied ml engineer, data generation & verification

aiml - sr backend engineer, data and ml innovation

aiml - sr machine learning engineer, data and ml innovation

store designer, worldwide grocery real estate

associate creative director (hybrid - seattle, wa)

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 sr machine learning engineer data and ml innovation

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Here's the job description with causal ML woven in: 
 
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. 
 
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. 
 
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. 
 
Key job responsibilities 
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. 
 
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. 
 
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. 
 
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. 
 
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. 
 
A day in the life 
We are hiring a Sr. Applied Scientist to drive our pricing optimization initiatives. We drive cross-domain and cross-system improvements through: 
 
<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> 
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. 
 
About the team 
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"> 
BASIC QUALIFICATIONS</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">
PREFERRED QUALIFICATIONS</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> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
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. 
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. 
USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually</div>

Sr. Applied Scientist, Pricing Science

Lightning AI

<div><div><h2 class="jobSectionHeader">Who We Are</h2>

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.

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.

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.
<h2 class="jobSectionHeader">
The Way We Work</h2>

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:
<ul>
<li>Move with Urgency: We move quickly, make thoughtful decisions, and keep momentum. We value action over perfection and learn by shipping.</li>
<li>Take Ownership: We own outcomes, not just our individual work. We make decisions that move the company forward and follow through.</li>
<li>Communicate Openly: We communicate directly, seek to understand, and create clarity for others. Honest conversations help us move faster together.</li>
<li>Build Great Teams: We lead by example, empower others, and create healthy teams where people can do their best work.</li>
<li>Raise the Bar: We're always improving ourselves. We learn from feedback, consistently challenge ourselves to grow, and focus on the work that matters most.</li>
<li>Think Long-Term: 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">What We're Looking For</h2>

Lightning AI is looking to hire an AI Platform Support Engineer 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.

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.

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.

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.<h2 class="jobSectionHeader"> 

What You'll Do</h2>

Work Directly With ML Engineers
<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>
Debug ML Infrastructure &amp; Distributed Workloads
<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>
Improve Reliability &amp; Platform Operations
<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>
What This Role Is Not

To set clear expectations:
<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>
This role is for engineers who enjoy solving difficult technical problems while working closely with other engineers. 

<h2 class="jobSectionHeader">
What You'll Need</h2>
<h3 class="jobSectionHeader">Required Qualifications</h3>
<h4 class="jobSectionHeader">Infrastructure &amp; Systems</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">ML Infrastructure Experience</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">Collaboration</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">Ideal Experience</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">Benefits and Perks</h2>

We offer a comprehensive and competitive benefits package designed to support our employees' health, well-being, and long-term success:
<ul>
<li>Comprehensive Health Coverage: Medical, dental, and vision coverage for employees and eligible dependents.</li>
<li>Meaningful Equity: RSUs that give employees a stake in the company's long-term success.</li>
<li>Retirement Savings: 401(k) matching (U.S.) and pension contributions (U.K.).</li>
<li>Flexible Time Off: Unlimited PTO, company holidays, and floating holidays to support work-life balance.</li>
<li>Company-Wide Winter Break: Two weeks of company closure each winter to disconnect and recharge.</li>
<li>Paid Parental &amp; Family Leave: Paid leave to support you and your family through life's important moments.</li>
<li>Professional Development: Annual learning and development allowance to support your professional growth.</li>
<li>Wellness Benefits: Wellness and work-from-home stipends to support your physical and mental well-being.</li>
<li>Sabbatical Program: Four weeks of paid sabbatical leave after four years of service.</li>
<li>Flexible Work: Flexible schedules and a hybrid work model for our office-based teams.</li>
<li>In-Office Meals: Complimentary meals at our office hubs.</li>
</ul>
Benefits may vary by location, team, and role. 


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.</div></div>

AI Platform Support Engineer (US)

<div><h2 class="jobSectionHeader">DESCRIPTION</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! 
 
Key job responsibilities 
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: 
<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">
BASIC QUALIFICATIONS</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">
PREFERRED QUALIFICATIONS</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> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
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. 
 
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. 
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. 
USA, CA, San Diego - 142,800.00 - 193,200.00 USD annually 
USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually</div>

Applied Scientist (GenAI/LLM), Sandstone

Amazon Web Services

<div><h2 class="jobSectionHeader">DESCRIPTION</h2>
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.
 
 
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.
 
 
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. 
 
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.
 
 
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.<h2 class="jobSectionHeader"> 
BASIC QUALIFICATIONS</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">
PREFERRED QUALIFICATIONS</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> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
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. 
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. 
USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually</div>

Sr. Applied Scientist, CAIT

Whatnot

<div>
 
 
 🚀 Join the Future of Commerce with Whatnot!
 
 
 
 
 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.
 
 
 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.
 
 
 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.
 
 
 
 💻 Role
 
 
 
 Data is crucial to Whatnot&rsquo;s mission to bring people together through commerce.
 
 
 As our newest
 
 Data Engineer
 
 , 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.
 
 
 
 On Any Given Day, You Will
 
 
 
 <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.
 
 
 </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.
 
 
 
 👋 You
 
 
 
 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.
 
 
 <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.
 
 
 </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.
 
 
 
 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.
 
 
 
 
 💰Compensation
 
 
 
 
 For Full-Time (Salary)
 
 
 
 
 US based applicants:
 
 $180,000/year to $260,000/year + benefits + equity.
 
 
 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.
 
 
 
 🎁 Benefits
 
 
 
 <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>
 
 
 💛 EOE
 
 
 
 
 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.
 
 
 Compensation Range: $180K - $260K
 
 
</div>

Data Engineer

Starbucks

<div>Now Brewing &ndash; Lead Data Scientist! #tobeapartner 
 
From the beginning, Starbucks set out to be a different kind of company. One that not only celebrated coffee and the rich tradition, but that also brought a feeling of connection. We are known for developing extraordinary leaders who share this passion and are guided by their service to others.
As a Lead Data Scientist on the Pricing Data Science team, you will lead the development of advanced pricing models and optimization algorithms that shape pricing decisions across US and Canada company-owned stores. You will drive the evolution of the pricing system by applying rigorous analytics, partnering with cross-functional teams, and influencing strategic workforce planning. Your work will directly impact pricing, and customer experience at scale.
As a lead data scientist, you will&hellip; 
Design and Architect the Future Pricing Ecosystem<ul><li>
Build a scalable, data-driven pricing framework that optimizes revenue.</li><li>
Incorporate predictive modeling, and ad hoc analyses into pricing framework. 
Drive Pricing and Revenue management data science</li><li>
Identify pricing and promotion potential through advanced analytics.</li><li>
Implement optimization strategies leveraging machine learning, simulation, and scenario planning.</li><li>
Partner with strategy and finance to align pricing tools with business goals. 
Mentor and Develop Talent</li><li>
Guide data scientists and senior data scientists in advanced analytics, optimization techniques, and business impact storytelling.</li><li>
Foster a culture of innovation and continuous improvement within the analytics team.</li></ul> 


We&rsquo;d love to hear from people with:<ul><li>
5+ years of progressive experience in data science, with a proven track record of end-to-end data product and model deployment that delivers measurable business impact.</li><li>
Strong foundation in machine learning and statistical techniques, including regression, classification, clustering, and causal inference.</li><li>
Advanced proficiency in Python, SQL, and cloud-based analytics platforms (e.g., Databricks, Azure), with experience developing production-grade data pipelines and model outputs.</li><li>
Excellent communication and data storytelling skills, with the ability to translate complex methodologies into clear, actionable insights through compelling visualizations and dashboards using tools like Tableau.</li><li>
Experience building in-house production systems in complex and data-rich domains.</li><li>
Mentoring experience</li></ul> 
Preferred Skills:<ul><li>
Expertise in building Bayesian elasticity models and causal inference</li><li>
Experience in optimization techniques such as linear programming, mixed-integer programming, or heuristic algorithms for decision support</li><li>
Background with PySpark and Databricks for distributed data processing and scalable analytics in cloud environments</li></ul><div> 
As a Starbucks partner, you (and your family) will have access to medical, dental, vision, basic and supplemental life insurance, and other voluntary insurance benefits. Partners have access to short-term and long-term disability, paid parental leave, family expansion reimbursement, paid vacation from date of hire*, sick time (accrued at 1 hour for every 25 hours worked), eight paid holidays, and two personal days per year. Starbucks also offers eligible partners participation in a 401(k) retirement plan with employer match, a discounted company stock program (S.I.P.), Starbucks equity program (Bean Stock), incentivized emergency savings, and financial well-being tools. Additionally, Starbucks offers 100% upfront tuition coverage for a first-time bachelor&rsquo;s degree through Arizona State University&rsquo;s online program via the Starbucks College Achievement Plan, student loan management resources, and access to other educational opportunities. You will also have access to backup care and DACA reimbursement. Starbucks will comply with any applicable state and local laws regarding employee leave benefits, including, but not limited to providing time off pursuant to the Colorado Healthy Families and Workplaces Act, and in accordance with its plans and policies. This list is subject to change depending on collective bargaining in locations where partners have a certified bargaining representative. For additional information regarding partner perks and more detailed information about benefits, go to starbucksbenefits.com. 
<ul><li>If you are working in CA, CO, IL, LA, ME, MA, NE, ND or RI, you will accrue vacation up to a maximum of 120 hours (190 in CA) for roles below director and 200 hours (316 in CA) for roles at director or above. For roles in other states, you will be granted vacation time starting at 120 hours annually for roles below director and 200 hours annually for roles director and above.</li></ul></div>
The actual base pay offered to the successful candidate will be based on multiple factors, including but not limited to job-related knowledge/skills, experience, geographical location, and internal equity. At Starbucks, it is not typical for an individual to be hired at the high end of the range for their role, and compensation decisions are dependent upon the facts and circumstances of each position and candidate.
We believe we do our best work when we're together, which is why we're onsite four days a week. 
Join us and inspire with every cup. Apply today! 
Starbucks Coffee Company is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, or protected veteran status, or any other characteristic protected by law. 
Qualified applicants with criminal histories will be considered for employment in a manner consistent with all federal, state and local ordinances. 
 
Starbucks Coffee Company is committed to offering reasonable accommodations to job applicants with disabilities. If you need assistance or an accommodation due to a disability, please contact us at applicantaccommodation@starbucks.com or 1(888) 611-2258.</div>

lead data scientist- Pricing, Data & Analytics (Seattle, WA)

Cloud Destinations

Job Title: VoIP Engineer IVNumber of Roles: 1Location: Seattle, WA - ***Onsite 2-3 days per week*** (flexible/negotiable which days &mdash; not fixed team days, just needs on-site coverage during business hours at all times)Duration: 6 months CTHJob Notes:Team Structure<ul><li>Team of 3 today: 2 Level 1 engineers + 1 Level 4 engineer</li><li>This role would be a 2nd Level 4 (backfill/additional operational support)</li><li>Responsibilities include mentoring/training the lower-level engineers, especially on the new project being implemented Experience Requirements</li><li>Minimum 7 years experience</li><li>Negotiable/flexible if candidate has direct NovelVox experience or comparable/equivalent experience</li><li>Degrees/certifications count toward &quot;points&quot; &mdash; there's a tradeoff between formal education/certs and hands-on work experience</li><li>They want someone who's already done this or something very similar &mdash; not someone learning on the job (this is a high-visibility project, no room for a learning curve) The Project needing to start ASAP after worker is identified</li><li>Client uses Epic (hosted instance via University of Washington partnership)</li><li>Patient Access team is implementing Epic Cheers (call management module) with CTI integration</li><li>Current stack: Cisco Finesse / UCCX. New state: UCCX stays as backend, but calling interface moves from Finesse into Epic Cheers, with NovelVox building the integration layer</li><li>Future/secondary work (not immediate): Cisco WebEx AI agents / NLP &mdash; not expected to be 100% of role, will also share in daily operations, design, architecture, and other essential duties per the job description</li><li>High visibility/political importance: identified as one of the organization's top 3 projects; described as critical to org credibility/reputation with partners Compensation</li><li>Conversion Salary range: $120K low &ndash; $190K high annually</li><li>Recruiters (client side) typically anchor offers at mid-range; going above requires justifying via considerable experience</li></ul>Job Summary:<ul><li>The Voice over IP Engineer IV provides Fred Hutchinson Cancer Center (FHCC) with expert level engineering, architecture, design, implementation, operations, management, and technical leadership of complex voice over IP systems.</li><li>At Fred Hutchinson Cancer Center, all employees are expected to demonstrate a commitment to our values of collaboration, compassion, determination, excellence, innovation, integrity, and respect.</li><li>The role will be focused on specific projects and will require the following skill-set in addition to the standard Knowledge, Skills and Abilities expected for this level of engineer.</li><li>Experienced with the design, deployment and support of pre-built CTI connectors such as NovelVox, SpinSci or AMC. NovelVox deployment with Epic and Cisco Unified Communications Manager is preferred.</li><li>Expertise in REST APIs, JSON, SOAP services, HL7 fundamentals, FHIR basics, XML, Authentication, OAuth, SAML and interface troubleshooting.</li><li>Cisco Contact Center Platforms: Expertise with Unified Contact Center Express, Webex Contact Center and Webex Customer Assist.</li><li>Expert in SIP trunking, dial plans, and intelligent omnichannel routing (voice, chat, email).</li><li>Webex AI &amp; Automation: Skill in implementing Webex AI agents, virtual assistants, and automated screen-pop.</li><li>Healthcare Contact Center Experience including patient identiy verification, HIPAA compliance, Protected Health Information,</li><li>Knowledge, Skills and Abilities</li><li>Experience in architecting, implementing, and configuring complex Cisco IPT solutions with Cisco Unified Call Manager (CUCM) clusters, Cisco Unity/Unity Connection Voicemail (CUC), Cisco IM &amp; Presence (CIMP), and voice gateways.</li><li>Expert knowledge and expertise in the design, consultation, long-term planning, installation, management, and repair of complex VoIP based network and telecommunication equipment, related applications, and associated services.</li><li>Expert knowledge and expertise on Cisco Routers, Structured Cabling, and LAN/WAN circuits; PRI, SIP, MPLS, FXO, FXS, and POTS.</li><li>Expert knowledge and expertise of the Cisco Unified Call Manager, IMP, Telepresence, IPCC, Unity, CCX, SRST, CUBE, secure voice concepts, and secure voice processes.</li><li>Ability to think strategically and to work effectively with a diverse group of co-workers and customers.</li><li>Ability to analyze and provide creative, innovative solutions for complex problems.</li><li>Proficient organizational, interpersonal, communication (written and verbal), and presentation skills.</li><li>Demonstrated engineering leadership abilities in a team environment with a proven record of positive contributions.</li><li>Ability to complete multiple tasks, set priorities, and manage to critical deadlines.</li><li>Must be able to work non-standard business hours and be on-call as necessary.</li><li>Knowledge and expertise Cisco Emergency Responder (CER) &amp; Cisco Unified Contact Center Express (UCCX).</li><li>Knowledge on Cisco network infrastructure, LAN/WAN circuits; QoS.</li><li>Able to anticipate customer needs, assess requirements, and identify new solutions to meet departmental/organizational goals.</li><li>Additional Cisco Certifications in any of the following: CCIE (strongly preferred), CCSA, CCNP, CCDP, CCIP.</li><li>Required Education and Experience</li><li>Bachelor&rsquo;s degree in computer science, engineering, information systems, or related field, or equivalent combination of education and experience.</li><li>Minimum seven (7) years' experience in Voice Operations and/or Voice Engineering.</li><li>Minimum five (5) years of experience in information technology administration or engineering, with three (3) years of experience in the information technology VoIP, telecommunications, or networking field.</li><li>Minimum three (3) years of experience directly managing IT telecommunication or infrastructure engineering and operational resources.</li><li>Minimum three (3) years of experience in leading teams and projects.</li><li>Primary Essential Duties</li><li>Responsible for development and maintenance of business-critical communications and/or network-based voice product systems, including planning, designing, and implementing scalable local and wide-area network solutions between multiple platforms and protocols (including IP and VoIP).</li><li>Responsible for monitoring and performance of enterprise platforms.</li><li>Oversees/troubleshoots voice issues and coordinates installation efforts with appropriate vendors and internal teams.</li><li>Leveraging expertise and experience, the incumbent will develop solutions that best align with FHCC&rsquo;s voice network requirements, identifying cost-effective implementation and long-term support strategies.</li><li>Provide Tier 2 support of internal voice and data communication systems.</li><li>Comply with departmental processes, such as incident management, change management and problem management.</li><li>Monitor and report on voice systems usage, availability, and performance.</li><li>Lead telephony system evaluations.</li><li>Collaborate with other members of IT staff and end users.</li><li>Follow VoIP engineering best practices and adhere to existing policies and procedures.</li><li>Design rack and cabinet equipment layout for server rooms and other telecommunications rooms.</li><li>Report, manage and troubleshoot issues with appropriate vendor tech-support staff.</li><li>Perform advanced-to-expert level configuration, troubleshooting and problem mitigation on all voice equipment, including wireless and network security equipment.</li><li>Work effectively with vendors, contractors, and other staff to coordinate system installations and provide quality assurance oversight.</li><li>Identify and maintain tools/applications for network monitoring, control, and reporting.</li><li>Lead short and long-range capacity planning.</li><li>Lead design, planning, and implementation of voice and data network systems.</li><li>Track telecommunication equipment software/firmware levels/revisions and lead efforts to upgrade accordingly.</li><li>Lead the evaluation of functionality/feature sets needed for telecommunications and direct selection of the correct hardware/software accordingly.</li><li>Utilize project planning and management skills to act as lead on large projects.</li><li>Perform in-depth telecommunications analysis, and provide evaluation, determination, and direction.</li><li>Provide advanced telecommunications/VoIP designs, including diagrams and documentation.</li><li>Provide guidance, direction, mentorship, and training to lower-level staff.</li><li>Perform 24/7 on-call support on a rotating basis and after-hours/weekend work for planned maintenance as required</li></ul>Pay: $85.00 - $90.00 per hourApplication Question(s):<ul><li>How many years you have experience with Voice Operations and/or Voice Engineering?</li><li>How many years you have experience with telecommunication?</li><li>Do you have experience with Cisco IPT solutions with Cisco Unified Call Manager (CUCM) clusters, Cisco Unity/Unity Connection Voicemail (CUC), Cisco IM &amp; Presence (CIMP), and voice gateways?</li></ul>Work Location: On the road

VoIP Engineer IV (Exp - 15+ years)

Explore 106+ Aiml sr machine learning engineer data and ml innovation in Seattle this August. Find roles across top companies and apply now to boost your career.