Senior Machine Learning Engineer I, AI & ML Platform

Title: Senior Machine Learning Engineer I, AI & ML Platform Location: San Francisco, CA (Hybrid)

Reporting to the Senior Engineering Manager of the AI & ML Platform team, this Senior Machine Learning Engineer will play a key part in building and scaling a centralized AI platform (services, tools, best practices, and more) that powers our care capabilities. This role is part of the AI & ML Platform team and is instrumental in stewardship of a shared foundation of AI and ML development at Spring Health.

Please note this is a hybrid role based in San Francisco with an expectation to be in the office 2-3 days per week at our 44 Montgomery location. Candidates must be based in the San Francisco area or able to relocate independently within 90 days of their start date. Occasional travel will be required for team on-sites.

What you'll do

• Collaborate to build and scale our AI platform, tooling, and best practices, enabling the rapid deployment of GenAI capabilities across the organization.
• Monitor and maintain the uptime of critical AI and ML tools to ensure high availability for key platform features.
• Contribute to backlog prioritization by identifying high-impact engineering opportunities that drive internal adoption of our centralized AI platform.
• Act as a technical advocate for the team by participating in on-call rotations, hosting internal office hours, and contributing to cross-functional AI working groups.
• Lead refactoring initiatives for key platform services to establish and enforce centralized coding standards for engineering contributors.
• Partner with machine learning teams to consult on and periodically modernize MLOps best practices.
• Drive cross-team collaboration to accelerate the adoption of AI and ML platform offerings, serving as a technical partner and consultant to feature teams.
• Troubleshoot and debug cloud (AWS and Azure) and Kubernetes (K8s) infrastructure issues to ensure the reliability and availability of platform services.
• Identify and recommend process optimizations to help the team effectively balance feature development, operational support, and internal consultations.

What success looks like in this role

• Maintain internal support service level agreements (SLAs) by achieving a 24-hour initial response time and ensuring active follow-up or resolution within 72 hours for cross-functional engineering inquiries.
• Reduce feature time-to-production for GenAI capabilities to meet established internal velocity targets.
• Improve internal Net Promoter Score (NPS) among engineering teams by reducing implementation friction and establishing centralized adoption standards for GenAI features.

What you'll bring

• Degree in Computer Science, Data Science, or a related field with a focus on Artificial Intelligence and Machine Learning.
• 4-6 years of Python development experience with GenAI and ML libraries and frameworks (such as LangChain, Pydantic, Scikit-Learn, and more).
• Experience maintaining and configuring engineering tools (third-party and in-house built), including deployment within a Kubernetes stack.
• Experience driving the adoption of generalized platforms with a continuous focus on improving internal Developer Experience (DX).
• Demonstrated ability to architect solutions for a full project as a lead prior to implementing a new feature, software, or tool in an enterprise environment while keeping project and organization constraints in mind.
• Demonstrated ability to mentor junior engineers and communicate complex technical ideas effectively to both technical and non-technical audiences to create buy-in and alignment.

Nice to have:

• Experience with MLOps and best practices for creating and deploying machine learning models.
• Background in a DevOps-style operational environment, including on-call rotations and cloud infrastructure management.
• Experience debugging and resolving issues within cloud environments (such as AWS or Azure) and Kubernetes clusters.
• 1-2 years of Ruby on Rails experience

The target base salary range for this position is $183,000 - $205,500, and is part of a competitive total rewards package including equity and benefits. Individual pay may vary from the target range and is determined by a number of factors including experience, location, internal pay equity, and other relevant business considerations. We review all employee pay and compensation programs annually using Radford Global Compensation Database at minimum to ensure competitive and fair pay.

Benefits provided by Spring Health:

Note: We have even more benefits than listed here and below, your recruiter will provide more in-depth information as you continue in the interview process. Benefits are subject to individual plan requirements and eligibility criteria.

• Health, Dental, Vision benefits start on your first day at Spring. You and your dependents also receive access to One Medical accounts HSA and FSA plans are also available, with Spring contributing up to $1K for HSAs, depending on your plan type.
• Employer sponsored 401(k) match of up to 2% for retirement planning
• A yearly allotment of no cost visits to the Spring Health network of therapists, coaches, and medication management providers for you and your dependents.
• We offer competitive paid time off policies including vacation, sick leave and company holidays.
• At 6 months tenure with Spring, we offer parental leave of 18 weeks for birthing parents and 16 weeks for non-birthing parents.
• Access to Noom, a weight management program—based in psychology, that’s tailored to your unique needs and goals.
• Access to fertility care support through Carrot, in addition to $4,000 reimbursement for related fertility expenses.
• Access to Wellhub,  which connects employees to the best options for fitness, mindfulness, nutrition, and sleep in one subscription
• Access to BrightHorizons, which provides sponsored child care, back-up care, and elder care
• Up to $1,000 Professional Development Reimbursement a year.
• $200 per year donation matching to support your favorite causes.