Top 33 Lead machine learning engineer Jobs in Washington State

Lead Principal Machine Learning Engineer
Oracle —Seattle, WA
- Computer Science
- 11+ years
- Research
13d
Senior Full-Stack Lead Engineer
NVIDIA —Seattle, WA
- $224,000 - $356,500 a year
- Full-time
- Computer science
- Azure
- Computer Science
Engineering Leader, Data Engineering
Apple —Seattle, WA
- $295,600 - $472,200 a year
- Continuous improvement
- Senior level
- Leadership
- Employee stock purchase plan
- Health insurance
Tech Lead-Machine Learning Engineer (Agent & Multi-Agent Systems) – AIGC Risk Intelligence
TikTok —Seattle, WA
- $232,560 - $427,500 a year
- 5 years
- Office
- Mentoring
- Paid parental leave
- Paid holidays
AIML - Sr Lead Engineer, Evaluation
Apple —Seattle, WA
- $205,400 - $374,300 a year
- Computer science
- Computer Science
- Bachelor of Science
- Employee stock purchase plan
- Health insurance
Tech Lead (Backend) - Trust and Safety (Seattle)
TikTok —Seattle, WA
- $232,560 - $427,500 a year
- Management
- Computer Science
- System design
- Paid parental leave
- Paid holidays
Display Integration Lead
Meta —Redmond, WA
- $173,000 - $245,000 a year
- Master's degree
- 8 years
- Mentoring
Lead Engineer
Raft Company Website —Tacoma, WA
- $180,000 - $230,000 a year
- Call employer
- Remote
- 6 years
- System design
- Travel
- Paid training
- Paid holidays
Tech Lead- E-commerce Recommendation Infrastructure - Seattle
TikTok —Seattle, WA
- $232,560 - $427,500 a year
- Computer Science
- 5 years
- System design
- Paid parental leave
- Paid holidays
Senior Program Lead, Digital Fraud & Abuse
GEICO —Seattle, WA
- $120,000 - $260,000 a year
- Full-time
- Continuous improvement
- APIs
- Senior level
Tech Lead / Principal Engineer, Creator Agent Algorithm Infrastructure
ByteDance —Seattle, WA
- $232,560 - $427,500 a year
- System design
- Office
- Fair chance
- Paid parental leave
- Paid holidays
Fab Engineering Lead
Meta —Redmond, WA
- $173,000 - $245,000 a year
- 8 years
- Fair chance
- Senior level
10h
Technical Lead - Compute Platform and Optimization
Overland AI —Seattle, WA
- $200,000 - $260,000 a year
- 7 years
- Computer Science
- Bachelor of Science
- Health insurance
- Dental insurance
10d
Tech Lead Software Engineer - AI Compute Infrastructure
ByteDance —Seattle, WA
- $232,560 - $427,500 a year
- Computer Science
- 5 years
- Bachelor of Science
- Paid parental leave
- Paid holidays
Tech Lead (Backend/Fullstack) - Trust and Safety (Seattle)
TikTok —Seattle, WA
- $202,160 - $368,220 a year
- Computer science
- Management
- Computer Science
- Paid parental leave
- Paid holidays
Lead Generative AI Data Engineer III
Deloitte —Seattle, WA
- $159,100 - $265,100 a year
- Full-time
- Management
- Computer Science
- Travel
Lead Software Engineer - Java Backend
JPMorganChase —Seattle, WA
- $152,000 - $215,000 a year
- Full-time
- 5 years
- Java
- Senior level
- Health insurance
- Tuition reimbursement
Product Lead, Gmail Life Management, Shopping, Ads, Wallet
Google —Seattle, WA
- $240,000 - $334,000 a year
- Full-time
- Office
- 3 years
- Bachelor's degree
- Paid holidays
- Disability insurance
9d
Software Development Engineer, Lead Management and Account-Based Marketing Tech
Amazon Web Services, Inc. —Seattle, WA
- $143,700 - $194,400 a year
- Full-time
- Computer science
- Computer Science
- Master's degree
- AD&D insurance
- Health insurance
Technical Lead - State Estimation
Overland AI —Seattle, WA
- $200,000 - $260,000 a year
- Computer science
- Computer Science
- Research
- Health insurance
- Dental insurance

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lead machine learning engineer jobs near washington state

Lead Principal Machine Learning Engineer

Oracle -
Seattle, WA

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Job Details

13 days ago

Qualifications

AI models
Containerization systems
Performance monitoring
Stakeholder engagement
Software engineering
Engineering development testing
High availability solutions design
IT operations
Cloud governance
Improving system uptime or availability
System performance optimization
AI platforms (beyond public GPTs)
Scalable systems
Computational framework
Enterprise software systems development
Prompt engineering
Infrastructure architecture design
Machine intelligence
Managing engineering teams
Cloud security
Application design
SRE
Data Security (Data management)
Incident management operations support
Design engineering
Cloud Native Design
Scalability
Production monitoring
Monitoring system implementation
Improving incident response processes

Full Job Description

The Senior Principal AI Agent / ML Software Engineer is a Senior Staff-level, hands-on technical leadership role responsible for defining, building, and operating next-generation AI systems on Oracle Cloud Infrastructure (OCI). This person will set architecture and engineering direction for production-grade agentic AI platforms, autonomous workflows, scalable inference infrastructure, and enterprise AI applications used in large-scale, business-critical environments.

This role requires a proven engineer who can translate ambiguous product and platform goals into durable technical strategy, lead multi-team execution without direct authority, and remain deeply hands-on in design, code, reviews, operations, and incident follow-up. The ideal candidate combines deep distributed systems experience with practical AI-native engineering, including orchestration of LLMs, tools, APIs, memory, retrieval, evaluation, guardrails, and cloud services. The expectation is to ship, scale, and operate reliable, secure, observable, and cost-aware AI platform systems while raising the technical bar for engineers across the organization..

Responsibilities

Serve as a senior technical owner for OCI AI platform capabilities, including agent execution, inference systems, model serving, AI workflow orchestration, evaluation, and observability.
Design, architect, and deliver scalable agentic AI systems capable of reasoning, planning, tool use, workflow execution, multi-step task orchestration, and safe human-in-the-loop escalation.
Build production-grade services for tool calling, agent memory, context management, Model Context Protocol (MCP) integration, vector retrieval, multi-agent coordination, policy enforcement, and evaluation.
Lead architecture across distributed services optimized for low latency, high throughput, GPU efficiency, reliability, cost, operability, and secure multi-tenant operation.
Define service boundaries, APIs, data models, state management, consistency tradeoffs, failure modes, SLIs/SLOs, rollout strategies, and operational readiness criteria for AI platform services.
Drive technical strategy across infrastructure, platform, security, data, and application engineering teams, converting broad goals into executable multi-quarter plans and measurable milestones.
Integrate AI agents securely and reliably with enterprise APIs, cloud services, databases, identity systems, secrets management, and external systems.
Establish AgentOps and LLMOps practices for tracing, monitoring, eval suites, regression testing, experimentation, safety guardrails, prompt/tool versioning, and production reliability.
Evaluate and operationalize emerging technologies in generative AI, agentic workflows, inference optimization, long-context systems, reasoning models, AI developer tooling, and agentic-first development.
Drive engineering excellence through code reviews, design reviews, test strategy, deployment automation, incident analysis, documentation, and AI-assisted development practices using tools such as Codex, Claude Code, Cursor, Copilot, or similar systems.
Mentor Staff and senior engineers, raise architectural standards, and influence engineering practices across OCI without requiring direct management authority.
Own critical production outcomes, including reliability, performance, security posture, cost efficiency, and supportability for the systems delivered.

Required Qualifications

Bachelor's, Master's, or Ph.D. in Computer Science, AI/ML, Engineering, or a related field, or equivalent practical experience.
12+ years of professional software engineering experience, including significant ownership of production systems; or equivalent experience demonstrating Senior Staff / Principal-level impact.
Proven track record as a Staff, Senior Staff, Principal, or equivalent technical leader influencing architecture and execution across multiple teams.
Deep experience designing, building, and operating high-scale distributed systems, cloud services, infrastructure platforms, or AI/ML platform services.
Hands-on experience with production AI systems, agentic AI applications, autonomous workflows, tool-using agents, multi-step orchestration, or multi-agent systems.
Practical experience with orchestration frameworks such as LangGraph, LangChain, CrewAI, AutoGen, LlamaIndex, or similar ecosystems.
Deep understanding of LLM application patterns, including prompt design, structured outputs, function/tool calling, context management, RAG, memory, tool safety, and evaluation.
Strong programming skills in Python and ability to contribute high-quality production code, reviews, tests, and debugging in complex distributed environments.
Strong expertise with Kubernetes, Docker, cloud-native infrastructure, service-to-service communication, scalability, fault tolerance, observability, and performance analysis.
Experience defining SLIs/SLOs, production readiness criteria, incident response practices, monitoring, tracing, experiments, and reliability programs for AI or distributed systems.
Strong understanding of AI safety, governance, security, and operational risks for autonomous or semi-autonomous systems, including data handling, access control, auditability, and human accountability.
Excellent written and verbal communication, with demonstrated ability to lead technical direction, resolve ambiguity, and influence senior stakeholders.

Preferred Qualifications

Experience optimizing large-scale GPU inference or training workloads for latency, throughput, utilization, availability, and cost.
Experience building or operating model serving, inference gateways, agent runtimes, workflow engines, developer platforms, or internal AI productivity platforms.
Experience integrating AI systems with enterprise APIs, databases, cloud services, vector databases, embeddings, retrieval systems, identity systems, and policy enforcement layers.
Experience with LLM fine-tuning, long-context systems, reasoning models, model routing, caching, batching, quantization, or emerging generative AI research.
Experience building evaluation frameworks for agentic systems, including offline evals, online experiments, golden tasks, adversarial testing, regression gates, and observability dashboards.
Experience using AI-assisted software development tools such as Codex, Claude Code, Cursor, Copilot, or similar systems in large-scale engineering environments.
Track record of defining architectural standards, platform capabilities, or engineering practices adopted across multiple teams or organizations.
Experience in enterprise, cloud infrastructure, regulated, security-sensitive, or mission-critical environments.

Apply Now

Refine Your Search

lead machine learning engineer jobs in washington state

Lead Principal Machine Learning Engineer

Senior Full-Stack Lead Engineer

Engineering Leader, Data Engineering

Tech Lead-Machine Learning Engineer (Agent & Multi-Agent Systems) – AIGC Risk Intelligence

AIML - Sr Lead Engineer, Evaluation

Tech Lead (Backend) - Trust and Safety (Seattle)

Display Integration Lead

Lead Engineer

Tech Lead- E-commerce Recommendation Infrastructure - Seattle

Senior Program Lead, Digital Fraud & Abuse

Tech Lead / Principal Engineer, Creator Agent Algorithm Infrastructure

Fab Engineering Lead

Technical Lead - Compute Platform and Optimization

Tech Lead Software Engineer - AI Compute Infrastructure

Tech Lead (Backend/Fullstack) - Trust and Safety (Seattle)

Lead Generative AI Data Engineer III

Lead Software Engineer - Java Backend

Product Lead, Gmail Life Management, Shopping, Ads, Wallet

Software Development Engineer, Lead Management and Account-Based Marketing Tech

Technical Lead - State Estimation

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