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)

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

data engineer

data engineer iii

machine learning engineer

Odins3

<div>
 Odins3
 
 
 Remote / Seattle
 
 
 Full-time
 
 
 Posted 931 days ago
 
 
 AI Development
 
 
 3+ years
 
 
 $160K - $220K
 
 
 0.05% - 0.2% equity
 
 
 Build and deploy ML models that power our AI website builder. Work on cutting-edge algorithms for automated web design and development.
 
 
 
 About This Role
 
 
 
 Join our ML Engineering team to build the brain behind our AI website builder. You'll develop sophisticated machine learning models that understand design principles, generate beautiful layouts, and create intelligent web experiences automatically.
 
 
 This role combines traditional ML engineering with creative applications in web design and development. You'll work with computer vision models for design analysis, NLP systems for content generation, and recommendation engines for design optimization.
 
 
 Our ML Engineers work across the full stack - from research and experimentation to production deployment and monitoring. You'll collaborate closely with our AI researchers, product team, and frontend engineers to bring cutting-edge ML capabilities to millions of users.
 
 
 
 Requirements
 
 
 
 <ul>
 <li>
 3+ years ML engineering experience
 </li>
 <li>
 Strong Python, TensorFlow/PyTorch background
 </li>
 <li>
 Experience with computer vision and NLP
 </li>
 <li>
 Knowledge of web technologies and design principles
 </li>
 <li>
 Experience with MLOps and model deployment
 </li>
 <li>
 Understanding of design systems and UI/UX principles
 </li>
 <li>
 Experience with cloud platforms (AWS, GCP, Azure)
 </li>
 <li>
 Knowledge of containerization and orchestration
 </li>
 <li>
 Experience with A/B testing and experimentation
 </li>
 <li>
 Strong data analysis and visualization skills
 
 
 </li>
 </ul>
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Develop ML models for automated web design
 </li>
 <li>
 Build recommendation systems for design elements
 </li>
 <li>
 Implement computer vision for image processing
 </li>
 <li>
 Deploy and monitor ML models in production
 </li>
 <li>
 Research and prototype new AI capabilities
 </li>
 <li>
 Optimize model performance and accuracy
 </li>
 <li>
 Build data pipelines for training and inference
 </li>
 <li>
 Collaborate with design team on AI-generated layouts
 </li>
 <li>
 Implement MLOps best practices
 </li>
 <li>
 Contribute to ML platform and infrastructure
 
 
 </li>
 </ul>
 
 Required Skills &amp; Technologies
 
 
 
 Python
 
 
 TensorFlow
 
 
 PyTorch
 
 
 Scikit-learn
 
 
 Pandas
 
 
 NumPy
 
 
 Computer Vision
 
 
 NLP
 
 
 MLOps
 
 
 Docker
 
 
 Kubernetes
 
 
 AWS
 
 
 PostgreSQL
 
 
 Redis
 
 
 Airflow
 
 
 Git
 
 
 Benefits &amp; Perks
 
 
 Competitive salary: $160K - $220K
 
 
 Equity package: 0.05% - 0.2%
 
 
 Comprehensive health coverage
 
 
 Unlimited PTO and flexible hours
 
 
 $4,000 annual learning budget
 
 
 Top-tier hardware and equipment
 
 
 Remote work stipend
 
 
 Conference attendance support
 
 
 Health and wellness benefits
 
 
 Team building and social events
 
 
 Work Environment &amp; Team
 
 
 Work Environment
 
 
 Fully remote with optional quarterly in-person sessions. Flexible schedule with some overlap with PST hours.
 
 
 Reporting Structure
 
 
 Reports to: Senior AI Developer. Collaborates with: AI Research team, Product Engineering, Design team.
</div>

Machine Learning Engineer - Web Development AI

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)

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

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

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Amazon's mission is to be Earth's most customer-centric company, and our Amazon Customer Service (CS) organization is an essential part of that mission. CS is one of the largest customer service organizations in the world with hundreds of thousands of associates providing support 24/7 in over 22 languages. 
 
The Network Solutions org within CS is building intelligent, adaptive systems that match customers to optimal experiences and continuously improve service quality at scale. The Journey Management (JM) Team within Network Solutions is looking for a Senior Business Intelligence Engineer to own the data modeling, analytics, and metrics infrastructure for Precision Match, the foundational capability that routes customers to the right support the first time for complete resolution. Journey Completion is the learning and corrective arm of Journey Management building Match Quality Intelligence that runs the flywheel to continuously refine matching quality and develops associates. 
 
In this role, you will design analytics-ready data models that transform raw pipeline data into structured datasets enabling inspection of matching quality at scale. You will own executive-facing dashboards and automated reporting for P0 Precision Match metrics including First Contact Resolution Rate, Transfer Rate, repeat contact rates, and attribution breakdowns. You will build BI capabilities that enable cross-functional partners to inspect matching performance and surface actionable insights without ad-hoc manual analysis. You will partner with engineering and science teams to define metrics governance, ensure data fidelity, and establish sources of truth for Precision Match reporting. 
The ideal candidate is a self-starter comfortable with ambiguity who communicates effectively across technical and non-technical teams and seeks to tell the story of the data with little direction. 
 
Key job responsibilities 
As the Senior Business Intelligence Engineer (BIE) for Journey Completion, you will be the single-threaded owner of the analytics and reporting infrastructure that powers Precision Match decision-making. You will operate at the intersection of data engineering, business intelligence, and product analytics, building systems that make matching performance visible, measurable, and actionable for leadership and cross-functional partners across a global CS network serving 500M+ annual contacts. 
 
Data Modeling and Dataset Engineering 
<ul><li>Design and build analytics-ready data models transforming raw pipeline data from matching, routing, and contact resolution systems into structured, queryable datasets.</li><li>Develop enriched datasets combining internal contact, associate, and routing data with attribution signals, applying data quality checks and ensuring source-to-consumption fidelity.</li><li>Work with cross-functional stakeholders to define and maintain sources of truth for Precision Match metrics. Obsessively monitor data fidelity and own resolution when issues arise.</li></ul> 
Executive Reporting and Dashboards 
<ul><li>Build and own executive-facing dashboards and automated reports (daily, weekly, monthly business reviews) for P0 Precision Match metrics and attribution breakdowns.</li><li>Create standardized reporting and operational templates driving consistent metrics tracking across Journey Management leadership.</li></ul> 
Analytics and Business Intelligence 
<ul><li>Develop analytics solutions enabling cross-functional partners to inspect matching performance, identify trends, and surface actionable insights at scale.</li><li>Manipulate and mine data from Redshift, MySQL, and other sources to perform root cause analyses on matching failures, answer complex business questions, and surface new insights on routing quality and associate performance.</li><li>Quantify Precision Match performance through attribution modeling distinguishing suboptimal matching from planning/supply factors and associate execution gaps.</li><li>Lead business discussions to share insights, challenge status quo, and provide forward-looking recommendations to enable strategic decision making and growth of Precision Match.</li></ul> 
AI-Enhanced Reporting 
<ul><li>Build AI-powered reporting solutions including LLM-assisted insights, automated narrative generation, and intelligent alerting extending what stakeholders can do independently with data.</li></ul> 
Cross-Functional Partnership 
<ul><li>Partner with engineering and science teams on metrics governance and data capture at source.</li><li>Translate complex business needs into clear data solutions across Journey Management, Precision Match science, and associate development teams.</li></ul> 
About the team 
You will be part of a Product and Technology team in Customer Service/ Network Solutions org building the intelligence to understand why a match results in a transfer or repeat contact, applying attribution logic that distinguishes suboptimal matching from planning/supply factors and associate execution gaps. You will work alongside SDEs, BIEs, Data Engineers, Scientists, TPMs, and Product Managers to build the closed-loop feedback system continuously optimizing matching and developing associates serving 500M+ annual contacts.</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>1+ years of SQL, ETL or Oracle experience</li><li>1+ years of developing automated reporting experience</li><li>5+ years of as a Data Analyst, Data Engineer, Business Intelligence Analyst, or a related occupation experience</li><li>Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, Statistics, Economics, or a related field</li><li>Experience with theory and practice of information retrieval, data science, machine learning and data mining</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience working directly with business stakeholders to translate between data and business needs</li><li>Experience managing, analyzing and communicating results to senior leadership</li><li>Experience programming to extract, transform and clean large (multi-TB) data sets</li><li>Experience with AWS technologies</li><li>Experience with theory and practice of design of experiments and statistical analysis of results</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 - 130,400.00 - 176,300.00 USD annually</div>

Senior Business Intelligence Engineer, Amazon Customer Service

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>
Are you passionate about building business insights that drive decision-making at the highest levels? Do you want to be part of a fast-paced, ambiguous environment and contribute to Amazon's Brand Protection charter? 
 
As a Sr. Business Intelligence Engineer, from Day 1, you will be challenged with solving complex and ambiguous data problems - from designing scalable data models and metric frameworks, to building executive-ready dashboards, owning pipeline architecture and driving the technical strategy for the data team. 
 
What are we looking for? 
<ul><li>You have a track record of end-to-end ownership and successfully delivering results in a fast-paced and dynamic business environment.</li><li>You are passionate about finding root causes, trends, and patterns and how they impact business. You use data to support your ideas and drive actionable outcomes, and draw inferences and conclusions based on data.</li><li>You should be able to work on complex initiatives, deal with ambiguity, and work with senior leaders.</li><li>You have extensive experience working with extremely large data sets and are comfortable with various tools and technologies to consume, extract, and transform data.</li><li>You have business communication skills to be able to work with product and program owners to understand key business questions, and are able to build solutions (analysis / reports / dashboards) that enable them to answer those questions quickly and accurately.</li><li>You are comfortable juggling competing priorities and handling ambiguity. You thrive in an agile and fast-paced environment on highly visible projects and initiatives.</li></ul>
- You have experience mentoring engineers and raising the technical bar for a team - through code reviews, architectural guidance, and leading by example. 
 
Key job responsibilities 
<ul><li>Be highly data driven, resourceful, and team oriented.</li><li>Translate analytic insights into actionable recommendations for business and clearly communicate strategic findings by translating complex technical concepts into business terms and vice versa.</li><li>Develop dashboards that provide insights into the health of the business, create analytics solutions to drive deep dives and uncover hidden risks/trends and recommend optimizations for future state.</li><li>Interact with internal program, product, engineering, data and science owners to gather requirements, structure scalable and performant data solutions and gain a deep understanding of key datasets.</li><li>Own the design, creation, and management of extremely large datasets and tune query performance against large and complex data sets.</li><li>Design, implement, and drive adoption of new analytic technologies and solutions and promote industry standard best practices.</li></ul>
- Serve as the technical lead for the Brand Protection data team - owning architectural decisions, mentoring engineers and analysts on best practices, query optimization, and data modeling. 
 
About the team 
 
The Brand Protection team is part of Amazon's WW Customer &amp; Partner Trust organization. Our vision is to use data provided by Brands in the Brand Registry to prevent Brands eligible for protections worldwide from ever seeing a listing on Amazon that has invalid data (e.g., misuse of trademarks, copyright) associated with their Brand. We strive to make Amazon the best way for Selling Partners to operate their businesses by protecting their intellectual property while reaching customers locally and globally.</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>10+ years of professional or military experience</li><li>5+ years of SQL experience</li><li>Experience programming to extract, transform and clean large (multi-TB) data sets</li><li>Experience with theory and practice of design of experiments and statistical analysis of results</li><li>Experience with AWS technologies</li><li>Experience in scripting for automation (e.g. Python) and advanced SQL skills.</li><li>Experience with theory and practice of information retrieval, data science, machine learning and data mining</li><li>Knowledge of data warehousing and data modeling</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience working directly with business stakeholders to translate between data and business needs</li><li>Experience managing, analyzing and communicating results to senior leadership</li><li>Experience with data visualization using Tableau, Quicksight, or similar tools</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 - 130,400.00 - 176,300.00 USD annually</div>

Business Intelligence Engineer III, Intellectual Property Protection

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