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

machine learning engineer

agentic ai engineer — healthcare ai Jobs in Seattle

agentic ai engineer — healthcare ai

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

senior ai ml data engineer layla ai

Expedia Group

<div>At Expedia Group, we help travelers explore the world, one journey at a time. As a global travel company powered by passionate people, trusted partnerships, and leading technology, we connect travelers, partners, and advertisers through our consumer brands, B2B network, and travel advertising business. 
 
Here, you'll do meaningful work that helps millions of people discover, book, and experience travel with more ease, confidence, and joy. Our five Behaviors-Traveler First, Think Big, Operate with Excellence, Ownership Mindset, and Succeed Together-help foster a supportive environment where people can grow their careers and have the flexibility, benefits, and support to do their best work. Join us and build for travelers everywhere.
Introduction to the Product Team
 
The Product Team creates high-quality end-to-end experiences for travelers, partners, and Expedia Group. Our customer-first mindset focuses on developing products that encourage loyalty and repeat business from our travelers and partners. We partner closely with teams across Expedia Group to achieve growth and results for our customers and company.
We connect Travelers to new experiences, through trusted relationships. We use the power of Expedia Group brands to empower strategic partners to nurture and grow the existing relationship with their audience. Strategic Partnerships and Affiliates breadth of solutions which include cashback, travel offers, loyalty exchange, co-branded sites, Affiliate APIs and EG&rsquo;s Affiliate Program, bring a partners&rsquo; audience onto EG sites, thereby increasing EG&rsquo;s traffic and exposure.
Introduction to the Layla Team
Layla is an AI-native travel-planning and booking company, now part of Expedia Group&rsquo;s Product organization. Through a conversational travel assistant, Layla helps travelers move from inspiration to a complete, bookable itinerary &mdash; flights, hotels, activities, and the day-by-day detail &mdash; in minutes. As part of Expedia Group, the team combines Layla&rsquo;s planning and personalization capabilities with Expedia Group&rsquo;s global supply, first-party traveler insights, marketplace scale, and booking technology.
The team is small and senior by design and operates with startup pace: you own a surface, ship it, and see the impact on real travelers within weeks &mdash; with decisions driven by data and AI tooling used in practice every day.
As a Senior AI / ML Data Engineer, you will build the data foundations that power Layla&rsquo;s AI-native travel experiences &mdash; the reliable pipelines, high-quality datasets, and experimentation and evaluation support that let the team ship and improve AI/ML systems in production with confidence.
In this role, you will:
<ul><li>Design, build, and operate reliable, scalable data pipelines that power Layla&rsquo;s AI-native trip-planning and booking experiences across Layla and Bellboy.
</li><li>Own data quality, reliability, and observability across critical datasets, establishing well-documented, trustworthy data models that other teams can confidently extend.
</li><li>Build and support the data foundations for experimentation and model evaluation, enabling honest, timely readouts that inform product and AI/ML decisions.
</li><li>Enable the production use of AI/ML systems &mdash; supporting feature and data availability, evaluation datasets, and monitoring &mdash; while applying AI/ML concepts responsibly.
</li><li>Partner closely with Product, Analytics, and ML/engineering teams to turn ambiguous questions into dependable data and self-serve answers.
</li><li>Advocate for engineering excellence in data &mdash; testing, documentation, and reusable patterns &mdash; and mentor other engineers on best practices.
</li></ul>Minimum Qualifications:
<ul><li>Bachelor&rsquo;s degree in Computer Science, Data Engineering, or a related technical field; or equivalent related professional experience.
</li><li>8+ years of relevant professional experience.
</li><li>Strong data engineering expertise, including advanced SQL and data modeling, and experience designing and operating production data pipelines.
</li><li>Proficiency with Python for data engineering work.
</li><li>Demonstrated ability to own data quality, reliability, and observability for critical datasets in production.
</li><li>Familiarity with supporting AI/ML systems in production &mdash; such as data/feature pipelines, evaluation datasets, or experimentation &mdash; and applying AI/ML concepts to real-world products responsibly.
</li></ul>Preferred Qualifications:
<ul><li>Experience with a modern data stack (for example, a transformation framework such as dbt, a cloud warehouse such as BigQuery or Snowflake, and BI tools such as Looker or Metabase).
</li><li>Experience building and maintaining experimentation frameworks and product analytics for a consumer product with real paid acquisition.
</li><li>Experience with attribution modeling, including an understanding of its limitations.
</li><li>Experience supporting production AI/ML or generative-AI systems (feature pipelines, evaluation, or monitoring), with attention to safety and responsible use.
</li><li>Experience using AI-assisted development tools (for example, Claude or similar) to improve productivity, quality, and delivery speed.
</li><li>Experience in travel, marketplace, or e-commerce domains, or building a data/analytics function from scratch.
</li></ul>Expedia Group is proud to offer a wide range of benefits to support employees and their families, including medical/dental/vision, paid time off, and an Employee Assistance Program. To fuel each employee&rsquo;s passion for travel, we offer a wellness &amp; travel reimbursement, travel discounts, and an International Airlines Travel Agent (IATAN) membership. View our full list of benefits .
The total cash range for this position in Seattle is $184,500.00 to $258,000.00. Employees in this role have the potential to increase their pay up to $295,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.&amp;#xa;The total cash range for this position in Austin is $184,500.00 to $258,000.00. Employees in this role have the potential to increase their pay up to $295,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role. 
 
Starting pay for this role will vary based on multiple factors, including location, available budget, and an individual&rsquo;s knowledge, skills, and experience. Pay ranges may be modified in the future. 
 
Benefits and perks
Expedia Group offers benefits and perks designed to support employees and their families, including medical, dental, and vision coverage, paid time off, an Employee Assistance Program, wellness and travel reimbursement, travel discounts, and International Airlines Travel Agent Network (IATAN) membership. Learn more about life at Expedia Group at https://careers.expediagroup.com/life . 
 
Accommodation requests
Expedia Group is committed to providing an inclusive and accessible recruiting experience. If you need an accommodation or adjustment due to a disability during the application or recruiting process, please submit a request at https://expedia.service-now.com/askeg?id=job_accommodation . 
 
About Expedia Group
Expedia Group includes three flagship consumer brands - Expedia, Hotels.com, and Vrbo - along with a leading B2B travel business and travel advertising offerings. Across our brands and business, we help travelers explore the world with confidence and ease. 
 
Important notice
Employment opportunities and job offers at Expedia Group will always come from Expedia Group's Talent Acquisition and hiring teams. Never share sensitive personal information unless you are confident of the recipient. Expedia Group does not extend job offers via email or messaging tools to individuals with whom we have not made prior contact. Our email domain is @expediagroup.com. The official place to find and apply for roles is https://careers.expediagroup.com/jobs/ . 
 
Equal Opportunity
Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, or any other characteristic protected by law. This employer participates in E-Verify. The employer will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee's I-9 to confirm work authorization.</div>

Senior AI / ML Data Engineer - Layla AI

<div>At Expedia Group, we help travelers explore the world, one journey at a time. As a global travel company powered by passionate people, trusted partnerships, and leading technology, we connect travelers, partners, and advertisers through our consumer brands, B2B network, and travel advertising business. 
 
Here, you'll do meaningful work that helps millions of people discover, book, and experience travel with more ease, confidence, and joy. Our five Behaviors-Traveler First, Think Big, Operate with Excellence, Ownership Mindset, and Succeed Together-help foster a supportive environment where people can grow their careers and have the flexibility, benefits, and support to do their best work. Join us and build for travelers everywhere.
Introduction to the Product Team
 
The Product Team creates high-quality end-to-end experiences for travelers, partners, and Expedia Group. Our customer-first mindset focuses on developing products that encourage loyalty and repeat business from our travelers and partners. We partner closely with teams across Expedia Group to achieve growth and results for our customers and company.
We connect Travelers to new experiences, through trusted relationships. We use the power of Expedia Group brands to empower strategic partners to nurture and grow the existing relationship with their audience. Strategic Partnerships and Affiliates breadth of solutions which include cashback, travel offers, loyalty exchange, co-branded sites, Affiliate APIs and EG&rsquo;s Affiliate Program, bring a partners&rsquo; audience onto EG sites, thereby increasing EG&rsquo;s traffic and exposure.
Introduction to the Layla Team
Layla is an AI-native travel-planning and booking company, now part of Expedia Group&rsquo;s Product organization. Through a conversational travel assistant, Layla helps travelers move from inspiration to a complete, bookable itinerary &mdash; flights, hotels, activities, and the day-by-day detail &mdash; in minutes. As part of Expedia Group, the team combines Layla&rsquo;s planning and personalization capabilities with Expedia Group&rsquo;s global supply, first-party traveler insights, marketplace scale, and booking technology.
The team is small and senior by design and operates with startup pace: you own a surface, ship it, and see the impact on real travelers within weeks &mdash; with decisions driven by data and AI tooling used in practice every day.
As a Senior Frontend Engineer, you will build the web experiences that bring Layla&rsquo;s conversational trip planning and booking to travelers &mdash; turning an AI-native travel assistant into fast, intuitive, and accessible interfaces.
In this role, you will:
<ul><li>Build reusable, component-based web interfaces with modern frontend frameworks (React / Next.js) that make Layla&rsquo;s conversational travel planning and booking intuitive, fast, and accessible.
</li><li>Translate product concepts, designs, and wireframes into high-quality, maintainable code, partnering closely with Product, Design, and backend engineering to ship features end to end.
</li><li>Develop performant, scalable, and reliable web applications, maintaining cross-browser compatibility and resolving performance bottlenecks.
</li><li>Run experiments and iterate quickly on the traveler experience, using data to guide UI and interaction decisions.
</li><li>Safely integrate and operate AI/ML-enabled capabilities in the web experience &mdash; such as assistant-driven planning, personalization, and recommendations &mdash; applying AI/ML concepts to real-world features responsibly.
</li><li>Advocate for engineering excellence, usability, accessibility (a11y), and quality, and help drive frontend architecture decisions and reusable patterns.
</li><li>Mentor other engineers through code review, technical design feedback, and knowledge sharing.
</li></ul>Minimum Qualifications:
<ul><li>Bachelor&rsquo;s degree in Computer Science or a related technical field; or equivalent related professional experience.
</li><li>8+ years of experience developing production-quality code in a professional software engineering role.
</li><li>Deep frontend/web development expertise, including JavaScript, React, HTML, and CSS, and experience building reusable, component-based user interfaces.
</li><li>Solid grounding in computer science fundamentals &mdash; data structures, algorithms, and object-oriented programming.
</li><li>Demonstrated ability to build fast, scalable, and reliable web applications with maintainable, testable frontend architecture.
</li><li>Familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to real-world products, with a focus on safely integrating these capabilities into web features.
</li></ul>Preferred Qualifications:
<ul><li>Experience with Next.js or similar modern React frameworks, including server-driven or server-rendered UI patterns.
</li><li>Experience partnering across the stack (for example, Node.js and APIs) to deliver end-to-end features.
</li><li>Experience building accessible (a11y) and inclusive web interfaces.
</li><li>Experience running experiments (A/B testing) and using product data to inform frontend decisions.
</li><li>Experience integrating AI/ML-enabled or generative-AI capabilities into web products, with attention to safety and responsible use.
</li><li>Experience using AI-assisted development tools (for example, Claude or similar) to improve developer productivity, code quality, and delivery speed.
</li><li>Experience in e-commerce, marketplace, or travel domains.
</li><li>Demonstrated ability to drive frontend architectural improvements and to mentor other engineers.
</li></ul>Expedia Group is proud to offer a wide range of benefits to support employees and their families, including medical/dental/vision, paid time off, and an Employee Assistance Program. To fuel each employee&rsquo;s passion for travel, we offer a wellness &amp; travel reimbursement, travel discounts, and an International Airlines Travel Agent (IATAN) membership. View our full list of benefits .
The total cash range for this position in Seattle is $184,500.00 to $258,000.00. Employees in this role have the potential to increase their pay up to $295,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.&amp;#xa;The total cash range for this position in Austin is $184,500.00 to $258,000.00. Employees in this role have the potential to increase their pay up to $295,000.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role. 
 
Starting pay for this role will vary based on multiple factors, including location, available budget, and an individual&rsquo;s knowledge, skills, and experience. Pay ranges may be modified in the future. 
 
Benefits and perks
Expedia Group offers benefits and perks designed to support employees and their families, including medical, dental, and vision coverage, paid time off, an Employee Assistance Program, wellness and travel reimbursement, travel discounts, and International Airlines Travel Agent Network (IATAN) membership. Learn more about life at Expedia Group at https://careers.expediagroup.com/life . 
 
Accommodation requests
Expedia Group is committed to providing an inclusive and accessible recruiting experience. If you need an accommodation or adjustment due to a disability during the application or recruiting process, please submit a request at https://expedia.service-now.com/askeg?id=job_accommodation . 
 
About Expedia Group
Expedia Group includes three flagship consumer brands - Expedia, Hotels.com, and Vrbo - along with a leading B2B travel business and travel advertising offerings. Across our brands and business, we help travelers explore the world with confidence and ease. 
 
Important notice
Employment opportunities and job offers at Expedia Group will always come from Expedia Group's Talent Acquisition and hiring teams. Never share sensitive personal information unless you are confident of the recipient. Expedia Group does not extend job offers via email or messaging tools to individuals with whom we have not made prior contact. Our email domain is @expediagroup.com. The official place to find and apply for roles is https://careers.expediagroup.com/jobs/ . 
 
Equal Opportunity
Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, or any other characteristic protected by law. This employer participates in E-Verify. The employer will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee's I-9 to confirm work authorization.</div>

Senior Frontend Engineer - Layla AI

Apple

Apple Services Engineering (ASE) powers the AI and LLM features behind experiences that hundreds of millions of users love every day. As these systems increasingly rely on human-in-the-loop evaluation, the quality of our products is directly constrained by the quality of our evaluation systems. We believe that to build exceptional AI, you need exceptional mechanisms to validate the signals used to train and evaluate them. 
 
Description 
 
The Human-centered AI, ML Data Quality Operations team is looking for a Senior Applied Scientist to join our growing team. We are building the systems and methodologies that make AI evaluation trustworthy, and scalable - directly shaping how Apple develops and validates AI across products and services. In this role, you will develop novel, scalable quality control solutions, working closely with cross-functional teams to ensure the data powering our AI/ML systems meets the highest standards of accuracy, consistency, and relevance. Your work will span the full lifecycle of quality assurance for AI and human judgments - from real-time validation and human-verified ground truth generation, to root-cause analysis that turns disagreements into corrective action. This role demands fluency across research thinking and engineering execution - you will prototype, validate, and ship. A strong point of view on when not to use a model or agent is as valued here as the ability to build one. 
 
&quot;,&quot;responsibilities&quot;:&quot;Design and implement scalable ground truth generation pipelines across varied task types, annotation modalities, and cold start conditions 
 
Build and maintain real-time monitoring systems that detect drift, distribution shifts, and quality degradation as they emerge across live evaluation and annotation pipelines. 
 
Design calibration frameworks that periodically re-anchor LLM evaluators against human-verified gold sets, correcting drift before it compounds. 
 
Build root-cause analysis tooling that surfaces disagreement patterns between automated and human judgments, and feeds findings directly into annotator training and guideline refinement. 
 
Partner closely with downstream users of these systems -ML teams, LLM-as-a-Judge (evaluator) developers, annotators - to ground design decisions in real feedback and usage patterns, not just architecture. 
 
Communicate findings and recommendations clearly to both technical and non-technical stakeholders 
 
Preferred Qualifications 
 
PhD in Computer Science, Machine Learning, Statistics, or a related field 
 
Experience in designing systems or tooling that are configurable and extensible by practitioners who did not build them 
 
Strong communication skills with the ability to influence technical direction across cross-functional teams 
 
Demonstrated passion for leveraging AI to improve work efficiency and scale 
 
Minimum Qualifications 
 
5+ years of industry experience in applied science or machine learning, with demonstrated experience building or operating production-grade evaluation, annotation, or quality-assurance pipelines. 
 
Hands-on experience designing ground truth generation pipelines across varied task types and annotation modalities, including cold-start scenarios with limited existing data. 
 
Experience building real-time monitoring or anomaly/drift detection systems for live data or ML pipelines. 
 
Working knowledge of evaluation methodology for generative AI - including LLM-as-a-judge design, meta-evaluation, failure mode analysis, and calibration/reference-guided grading techniques 
 
Strong software engineering fundamentals and proficiency in Python and relevant ML frameworks, with production experience building, deploying, and monitoring LLM-based pipelines and agents. 
 
Demonstrated ability to work directly with downstream users/stakeholders to incorporate feedback into system design, and to communicate findings clearly to both technical and non-technical audiences. 
 
MS or PhD in Computer Science, Machine Learning, Statistics, or a related quantitative field, or equivalent practical experience. 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $142,300 and $263,300, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Sr. Applied Scientist, AI Evaluation & Quality Systems

Deloitte

<div>
 Three hundred fifty million Americans rely on a healthcare system whose decision-making has become slow, costly, and adversarial - care delayed by prior authorization and paperwork, claims that misfire, clinical decisions made without the right information at the right moment, and patients who struggle to navigate or afford the care they need. Deloitte has a new AI-first effort, backed by $1B in committed investment, building the reasoning models and agentic systems to rebuild how that system decides - across payers, providers, and life sciences, and for the patients they serve - so that care is faster, fairer, and far less wasteful. This is not AI applied at the margins. It is a ground-up rebuild of the decision-making machinery behind American healthcare, at national scale.
 
 
 This is an early, well-funded build. You will own agent systems end to end - from architecture through production - and your work ships into live clinical and operational settings within your first months, not into a lab.
 
 
 As an Agentic AI Engineer, you will design, build, and operationalize the LLM- and SLM-powered systems behind real healthcare decisioning - the reasoning, orchestration, retrieval, memory, and control layers that let intelligent agents operate reliably across the hardest decisions in the industry: clinical reasoning, prior authorization and claims integrity, care navigation, and the operational workflows that run across payers, providers, and life sciences. This is not a prompt-only role. We are looking for builders who think deeply about system behavior, grounding, and reliability where a wrong action has real consequences for patients and the clinicians who serve them.
 
 
 You do not need a healthcare background. We pair every engineer with clinical and domain experts and teach you the domain - you bring the agentic engineering depth.
 
 
 We hire on demonstrated depth, not years - the level you join at is determined through our interview process, based on the depth and judgment you demonstrate, not your years in a title.
 
 
 Work you'll do
 
 
 Agent architecture &amp; orchestration
 
 
 <ul>
 <li>
 Design and implement agentic systems capable of multi-step reasoning, planning, tool use, and workflow execution against complex, regulated operational processes.
 </li>
 <li>
 Build stateful workflows using frameworks such as LangGraph and LangChain - including branching, retries, self-correction, human-in-the-loop checkpoints, and reusable orchestration patterns.
 </li>
 <li>
 Engineer for long-horizon reliability - multi-step task completion, recovery from compounding errors, planning under uncertainty, and robust tool use when individual steps fail.
 </li>
 <li>
 Build the reasoning behind regulated decisions - policy- and criteria-grounded outputs, structured proposer/critic/judge-style review, and auditable rationales for high-stakes decisions across the industry, from clinical review and prior authorization to claims integrity and care management.
 
 
 </li>
 </ul>
 Retrieval, grounding &amp; context engineering
 
 
 <ul>
 <li>
 Develop end-to-end Retrieval-Augmented Generation (RAG) pipelines: ingestion, chunking, embeddings, vector and hybrid retrieval, reranking, contextual compression, and grounding strategies.
 </li>
 <li>
 Engineer memory and context management - conversational state, persistent memory, retrieval-aware context assembly, and token-efficient context selection.
 </li>
 <li>
 Apply modern context-delivery patterns (e.g., MCP-style tool/context interfaces) so agents access the right information at the right time.
 
 
 </li>
 </ul>
 Reliability, evaluation &amp; safety
 
 
 <ul>
 <li>
 Implement observability and tracing for prompts, tool calls, retrieval quality, agent traces, failures, drift, latency, and production behavior.
 </li>
 <li>
 Apply guardrails, safety controls, and failure-handling to reduce hallucinations and unsafe actions.
 </li>
 <li>
 Evaluate agents at the trajectory and task level - multi-step task success, failure-mode and regression analysis, and sandboxed test environments - alongside retrieval- and generation-quality metrics, automated checks, and human review.
 </li>
 <li>
 Engineer healthcare-grade safety - deployment eval gates, human-oversight and escalation models, auditability and traceability for regulated decisions, and PHI/HIPAA-aware data handling.
 
 
 </li>
 </ul>
 Integration &amp; production craft
 
 
 <ul>
 <li>
 Build integrations with internal and external tools, APIs, enterprise systems, databases, and model providers so agents operate safely within real business workflows.
 </li>
 <li>
 Deliver production-quality code with strong practices in testing, CI/CD, logging, versioning, and documentation; make architecture decisions that balance quality, safety, latency, cost, and model risk.
 </li>
 <li>
 Partner with our modeling and post-training engineers to improve model behavior for tool use, grounding, and long-horizon reasoning - through evaluation-driven feedback and, where it helps, fine-tuned or reasoning-optimized models.
 </li>
 <li>
 Translate ambiguous, high-complexity operational processes into robust system logic and reusable AI patterns; stay current with advances in agentic systems and translate research into practical engineering decisions.
 
 
 </li>
 </ul>
 The team
 
 
 Deloitte brings together AI researchers, modeling and platform engineers, architects, clinical and domain specialists, and product leaders to build, deploy, and operate verticalized AI systems across software, data, models, and cloud infrastructure - engineered for one of the most complex operating environments in the world. The work spans the healthcare industry - payers, providers, and life sciences - and involves genuinely hard reasoning problems, nuanced operational workflows, and a high bar for reliability, with little tolerance for shallow or unreliable outputs. We pair frontier AI research with production-grade engineering, and we ship into real clinical and operational settings rather than leaving models in the lab.
 
 
 
 Required Qualifications
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, Engineering, Data Science, Computational Linguistics, or a related field.
 </li>
 <li>
 Demonstrated depth building and shipping production agentic systems - this is your primary craft, not a recent exploration. We weigh shipped systems, research, model releases, and open source over years in a title; expect strong software/ML fundamentals plus substantial, recent hands-on agentic work.
 </li>
 <li>
 Strong, hands-on experience building production agent systems with modern orchestration - LangGraph/LangChain or equivalent, including custom orchestration.
 </li>
 <li>
 Experience designing and optimizing end-to-end RAG systems: indexing, retrieval, reranking, grounding, and evaluation.
 </li>
 <li>
 Strong understanding of memory and context management, including context windows, retrieval-driven context assembly, persistent memory, and high-signal context selection.
 </li>
 <li>
 Deep, practical understanding of LLM behavior - strengths, limitations, hallucination risks, reasoning constraints, and latency/cost trade-offs - and the evaluation methods used to measure them.
 </li>
 <li>
 Experience evaluating and debugging agent behavior - task-success and trajectory analysis, not just output quality.
 </li>
 <li>
 Strong Python engineering skills and modern software practices: testing, CI/CD, version control, and API integration; experience implementing observability, tracing, and debugging for LLM-based systems in production.
 </li>
 <li>
 Hands-on experience with at least one frontier model platform (e.g., Anthropic, Google, OpenAI) and/or open-weight/self-hosted models (e.g., Llama via vLLM), including production tool use and agent capabilities.
 </li>
 <li>
 Ability to travel 0-50%, on average, based on the work you do and the clients and industries/sectors you serve.
 </li>
 <li>
 Limited immigration sponsorship may be available.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience with multi-agent systems and agent collaboration patterns.
 </li>
 <li>
 Familiarity with vector databases and retrieval infrastructure such as Pinecone, Weaviate, or Milvus.
 </li>
 <li>
 Exposure to model adaptation and fine-tuning techniques such as LoRA or QLoRA.
 </li>
 <li>
 Understanding of traditional NLP concepts: tokenization, semantic similarity, entity extraction, summarization, and transformer fundamentals.
 </li>
 <li>
 Experience operating in highly regulated, high-stakes, or operationally complex environments; healthcare exposure - clinical, payer, or life-sciences workflows, or standards such as FHIR - is a plus, not a requirement.
 </li>
 <li>
 Demonstrated habit of staying current with AI research, benchmarks, and emerging engineering patterns.
 
 
 </li>
 </ul>
 
 Compensation
 
 
 
 Base salary is benchmarked to leading technology companies rather than traditional consulting scales, and the role carries a substantial performance-based incentive opportunity designed to grow with the value you help create - startup-style upside, with the backing of a committed, well-capitalized platform. The estimated base salary range is $110,700-$372,900 (not adjusted for geographic differential); actual base pay depends on your skills, experience, and level, and you may also be eligible for a discretionary annual incentive based on individual and organizational performance.
</div>

Agentic AI Engineer — Healthcare AI

turing

<div><div><h1 class="jobSectionHeader">About Turing</h1>

Turing's mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com.</div><div></div> 
Turing is looking for a Senior Technical Recruiter to join our embedded Research Engineering Recruitment Pod. In this role, you will work side-by-side with our Research Scientists, Research Engineers, and AI leadership to source, engage, and close the talent building at the frontier of AI.

This is not a high-volume, transactional recruiting role. The talent pool for elite Research Engineers and Forward-Deployed Engineers is highly concentrated, hyper-competitive, and continuously targeted by frontier labs. You will act as an embedded strategic partner, mapping passive talent ecosystems across academia, quantitative research, and open-source networks, developing technically informed candidate pipelines, and orchestrating bespoke closing strategies for candidates who do not move through standard corporate hiring funnels.
<h3 class="jobSectionHeader">
The Anti-Sell</h3>

This is a high-urgency recruiting role. You will compete head-to-head with frontier AI labs and hyperscalers for candidates who are often managing multiple highly competitive offers. Winning in this market requires deep technical literacy, exceptional speed, and continuous market intelligence.

This isn't for everyone. But if you want to work on an elite team to hire the most sought-after talent in frontier AI and help build the teams defining what comes next in the field, this role may be for you!
<h3 class="jobSectionHeader">
What You'll Do</h3>
<h4 class="jobSectionHeader">Sourcing &amp; Pipeline Building</h4>
<ul><li>Look beyond standard keyword searches by continuously tracking arXiv preprints, GitHub activity, OpenReview submissions, and open-source contributions.</li>
<li>Map and cultivate passive talent ecosystems across top PhD programs (Stanford, MIT, CMU), frontier research labs and high-growth AI startups.</li>
<li>Build proactive candidate pipelines long before formal requisitions open, using emerging signals across research, open-source, and professional networks to identify and engage exceptional talent early.</li>
</ul><h4 class="jobSectionHeader">Engaging Incredibly Hard-to-Reach Talent</h4>
<ul><li>Reach passive researchers, Research Engineers, and Forward-Deployed Engineers who do not respond to generic recruiter outreach.</li>
<li>Demonstrate the technical fluency to assess candidate relevance, understand research contributions, and partner with technical leaders on candidate calibration across relevant technical domains.</li>
</ul><h4 class="jobSectionHeader">Closing Highly Sought-After Talent</h4>
<ul><li>Partner directly with the CEO, CTO, and research leaders to design and execute individualized closing playbooks for highly sought-after talent.</li>
<li>Win contested offers by understanding each candidate's motivations and leveraging the aspects of the opportunity that matter most to them.</li>
</ul><h3 class="jobSectionHeader">What We're Looking For</h3>
<ul>
<li>Technical Recruiting Track Record: 4+ years of full-lifecycle technical recruiting experience, with proven depth in AI/ML, Research Engineering, Distributed Systems, or Forward-Deployed Engineering.
</li>
<li>Domain Literacy: Ability to speak credibly with top researchers and technical leaders.
</li>
<li>Proven Closer: Demonstrated track record of personally sourcing and closing highly sought-after candidates against competing offers from frontier labs or hyperscalers.
</li>
<li>Compensation &amp; Equity Fluency: Strong understanding of private-company equity, technical compensation, and competitive market benchmarking.
</li>
<li>High Ownership &amp; Startup Speed: Ability to operate with high urgency in a fast-moving AI research environment.
</li>
</ul><h3 class="jobSectionHeader">What Success Looks Like</h3>
<ul><li>Compounding Talent Density: Continuously raising the technical caliber and execution velocity of Turing's Research Engineering and Forward-Deployed AI teams.</li>
<li>High Win Rates: Consistently converting highly sought-after candidates and maintaining strong offer acceptance rates in contested searches.</li>
<li>Trusted Technical Partnership: Earning deep trust with research directors and technical leads, acting as an embedded advisor who understands the research roadmap.</li></ul><div><h2 class="jobSectionHeader"> 
Values</h2>
<ul><li>We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. 
</li>
<li>We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection 
</li>
<li>We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity.</li>
</ul><h2 class="jobSectionHeader">Advantages of joining Turing</h2>
<ul><li>Work at the frontier of AI, helping the world's leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks. 
</li>
<li>Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS. 
</li>
<li>Bring frontier AI innovation to the enterprise, applying lessons learned from leading AI labs to solve real-world business challenges. 
</li>
<li>Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies. 
</li>
<li>Move at the pace of AI innovation, with the speed, ownership, and impact of a startup.</li></ul> 


Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace and celebrate authenticity, so if you're excited about this role but your past experience doesn't align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.
<div>
For applicants from the European Union, please review Turing's GDPR notice here.</div></div></div>

Senior Technical Recruiter - Research Engineering Pod

Amazon Web Services

Job OverviewWe are seeking a dynamic and innovative Machine Learning Engineer to join our forward-thinking team. In this role, you will be at the forefront of developing, implementing, and optimizing advanced machine learning models and AI solutions. Your expertise will drive data-driven decision-making, enhance predictive analytics, and support scalable AI applications across diverse platforms. This position offers an exciting opportunity to work with cutting-edge technologies in big data systems, cloud services, and natural language processing to shape the future of intelligent solutions.Duties<ul><li>Design, develop, and deploy machine learning models utilizing frameworks such as TensorFlow and other AI tools to solve complex business problems.</li><li>Implement scalable data pipelines using ETL processes and big data systems like Hadoop and Spark to prepare data for analysis and model training.</li><li>Conduct statistical modeling and analysis to extract insights from large datasets, supporting research and strategic initiatives.</li><li>Collaborate with cross-functional teams to integrate AI models into production environments using cloud services such as AWS and machine learning cloud platforms.</li><li>Optimize model performance through rigorous evaluation, tuning, and validation techniques including model evaluation metrics and predictive modeling analysis.</li><li>Develop natural language processing applications to enhance text analysis capabilities within products or research projects.</li><li>Maintain comprehensive documentation of algorithms, processes, and system architecture while ensuring scalability and robustness of deployed models.</li></ul>Skills<ul><li>Proficiency in programming languages such as Python, Java, C, R, and Bash (Unix shell) for data analysis, model development, and automation tasks.</li><li>Extensive experience with machine learning frameworks including TensorFlow, Spark implementation, and generative AI techniques.</li><li>Strong knowledge of big data technologies like Hadoop, Spark, Talend, and SQL databases for efficient data mining and analytics.</li><li>Expertise in statistical analysis tools such as SAS or R for research-driven insights and statistical modeling.</li><li>Hands-on experience with AI implementation in cloud environments like AWS or other machine learning cloud services for scalable deployment.</li><li>Familiarity with database design principles, SQL query optimization, and data analytics to support complex data workflows.</li><li>Understanding of natural language processing (NLP), AI models development, model training strategies, evaluation methods, and deployment best practices.</li><li>Knowledge of data integration tools such as Talend for efficient ETL workflows; experience with Looker for data visualization is a plus.</li><li>Ability to work on large-scale big data systems involving scalability challenges in real-time analytics environments.</li></ul>Join us to leverage your expertise in machine learning/AI-based analysis to revolutionize how data transforms into actionable insights!Pay: $192,000.00 - $229,000.00 per yearBenefits:<ul><li>401(k)</li><li>Flexible spending account</li><li>Parental leave</li><li>Relocation assistance</li></ul>Work Location: In person

Machine Learning Engineer

Explore 16+ Senior ai ml data engineer layla ai in Seattle this September. Find roles across top companies and apply now to boost your career.

16 senior ai ml data engineer layla ai jobs In Seattle

Senior AI / ML Data Engineer - Layla AI

Senior Frontend Engineer - Layla AI

Sr. Applied Scientist, AI Evaluation & Quality Systems

Sr. Applied Scientist, AI Evaluation & Quality Systems

Agentic AI Engineer — Healthcare AI

Senior Technical Recruiter - Research Engineering Pod

Machine Learning Engineer