Staff AI/ML Engineer

About the role

As a Staff AI/ML Engineer, you will define the Technology AI/ML engineering approach and solve complex model development, training infrastructure, and AI system reliability challenges. You will set domain standards for ML experimentation practices, model evaluation, responsible AI deployment, and GenAI system architecture, operating as the highest individual contributor in the AI/ML engineering discipline and influencing technical direction at an organizational level. In this role, you will shape AI product strategy through deep technical expertise, develop the next generation of senior ML engineering leaders, and serve as a recognized authority both internally and in the broader AI/ML community. You will set the bar for technical innovation, responsible AI, and engineering excellence across multiple teams.

Responsibilities

• Define the technical vision and strategy for AI/ML engineering platform spanning model development, training infrastructure, serving, evaluation, and governance
• Solve complex AI/ML engineering challenges including large-scale training instability, serving reliability at massive scale, and novel model quality problems with no established playbook
• Establish AI/ML engineering standards for experiment reproducibility, model evaluation rigor, responsible AI practices, and production reliability adopted across all teams
• Drive capability in frontier AI/ML techniques including large-scale foundation model training, advanced fine-tuning methods, and next-generation GenAI system design
• Consult with applied science leaders and enterprise architects on AI system architecture decisions providing expert guidance on feasibility, trade-offs, and long-term engineering implications
• Lead technical design reviews providing expert guidance on ML system architecture, training strategy, and platform evolution
• Mentor senior and staff engineers across the domain developing AI/ML engineering leaders and building organizational capability

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, or related technical field, or equivalent experience; advanced degree (Master’s or PhD) preferred
• 9–12 years of AI/ML engineering experience defining AI/ML engineering strategy and establishing standards across the organization, or equivalent, which includes educational experience (e.g., PhD degree)
• Demonstrated ability to set software engineering standards for complex AI/ML application development including design patterns, testing frameworks, and service architecture adopted across all AI/ML engineering teams
• Demonstrated ability to set strategy for design and implementation of highly complex models with multiple AI/ML components, training infrastructure, and evaluation rigor at enterprise scale
• Demonstrated ability to set MLOps strategy including CI/CD standards, serving platform architecture, and deployment practices
• Demonstrated ability to set GenAI engineering strategy including foundation model selection, fine-tuning infrastructure, and responsible AI standards
• Track record mentoring senior and staff engineers; define the mentorship and technical development strategy for the AI/ML engineering domain
• Experience with common ML tools and frameworks and implementation such as Python, Spark, Airflow, MLFlow, feature stores, cloud ML platforms

Must-haves

• Acknowledge the presence of choice in every moment and take personal responsibility for your life
• Possess an entrepreneurial spirit and continuously innovate to achieve great results
• Communicate with honesty and kindness and create the space for others to do the same
• Lead with courage, knowing the possibility of greatness is bigger than the fear of failure
• Foster connection by putting people first and building trusting relationships
• Integrate fun and joy as a way of being and working; it doesn’t take yourself too seriously

Pay

The typical hiring range for this position is $211,880 – $278,090 annually; the base pay offered is based on market location and may vary depending on job-related knowledge, skills, experience, and internal equity. As part of our total rewards offering, permanent employees in this position may be eligible for our competitive annual bonus program and equity offerings, subject to program eligibility requirements.

Benefits

• Extended health and dental benefits, and mental health plans
• Paid time off
• Savings and retirement plan matching
• Generous employee discount
• Fitness & yoga classes
• Parenthood top-up
• Extensive catalog of development course offerings
• People networks, mentorship programs, and leadership series

Schedule

Work is performed onsite, minimum 4 days per week.