{"id":1769447,"url":"https://alion.io/job/spring-health-senior-machine-learning-engineer-i-ai-ml-platform-2","title":"Senior Machine Learning Engineer I, AI & ML Platform","company":{"id":1223,"name":"Spring Health","domain":"springhealth.com","url":"https://alion.io/company/spring-health","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":183000,"max":205000,"currency":"USD","period":"year","gross":null,"usd_annual":205000},"salary_estimate":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"Machine Learning","optional":false},{"name":"Pydantic","optional":false},{"name":"Python","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Ruby","optional":true},{"name":"Ruby on Rails","optional":true}],"status":"live","first_seen_at":"2026-08-13T17:48:03Z","employer_posted_date":"2026-08-13","last_verified_at":"2026-10-20T02:54:08Z","board_verified":true,"closed_at":null,"days_open":67,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":67},"description":"Our mission: eliminating every barrier to mental health.\nSpring Health is a global mental health company on a mission to eliminate every barrier to mental health. We're building a world where getting support is simple, personal, and built around the person, so care can continue through every job, move, health plan, and life stage.\nOur AI-native platform helps us deliver personalized support across self-guided tools, coaching, therapy, medication management, and specialty care. With outcomes independently validated by JAMA Network Open and the Validation Institute, Spring Health reaches more than 170 million people worldwide through leading employers, health plans, and partners.\nAs an AI-native company, we believe technology should expand the reach, quality, and humanity of care. Every Spring Health team member is expected to use AI tools thoughtfully, apply human judgment to AI outputs, and keep building AI fluency in ways that support their role and our mission.\nReporting 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.\nPlease 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.\nWhat you'll do\nCollaborate to build and scale our AI platform, tooling, and best practices, enabling the rapid deployment of GenAI capabilities across the organization.\n\nMonitor and maintain the uptime of critical AI and ML tools to ensure high availability for key platform features.\n\nContribute to backlog prioritization by identifying high-impact engineering opportunities that drive internal adoption of our centralized AI platform.\n\nAct 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.\n\nLead refactoring initiatives for key platform services to establish and enforce centralized coding standards for engineering contributors.\n\nPartner with machine learning teams to consult on and periodically modernize MLOps best practices.\n\nDrive cross-team collaboration to accelerate the adoption of AI and ML platform offerings, serving as a technical partner and consultant to feature teams.\n\nTroubleshoot and debug cloud (AWS and Azure) and Kubernetes (K8s) infrastructure issues to ensure the reliability and availability of platform services.\n\nIdentify and recommend process optimizations to help the team effectively balance feature development, operational support, and internal consultations.\n\nWhat success looks like in this role\nMaintain 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.\n\nReduce feature time-to-production for GenAI capabilities to meet established internal velocity targets.\n\nImprove internal Net Promoter Score (NPS) among engineering teams by reducing implementation friction and establishing centralized adoption standards for GenAI features.\n\nWhat you'll bring\nDegree in Computer Science, Data Science, or a related field with a focus on Artificial Intelligence and Machine Learning.\n\n4-6 years of Python development experience with GenAI and ML libraries and frameworks (such as LangChain, Pydantic, Scikit-Learn, and more).\n\nExperience maintaining and configuring engineering tools (third-party and in-house built), including deployment within a Kubernetes stack.\n\nExperience driving the adoption of generalized platforms with a continuous focus on improving internal Developer Experience (DX).\n\nDemonstrated 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.\n\nDemonstrated ability to mentor junior engineers and communicate complex technical ideas effectively to both technical and non-technical audiences to create buy-in and alignment.\n\nNice to have:\nExperience with MLOps and best practices for creating and deploying machine learning models.\n\nBackground in a DevOps-style operational environment, including on-call rotations and cloud infrastructure management.\n\nExperience debugging and resolving issues within cloud environments (such as AWS or Azure) and Kubernetes clusters.\n\n1-2 years of Ruby on Rails experience\n\nBenefits provided by Spring Health:\nNote: 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. \n\nHealth, 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.\n\nEmployer sponsored 401(k) match of up to 2% for retirement planning\n\nA yearly allotment of no cost visits to the Spring Health network of therapists, coaches, and medication management providers for you and your dependents.\n\nWe offer competitive paid time off policies including vacation, sick leave and company holidays.\n\nAt 6 months tenure with Spring, we offer parental leave of 18 weeks for birthing parents and 16 weeks for non-birthing parents.\n\nAccess to Noom, a weight management program-based in psychology, that’s tailored to your unique needs and goals.\n\nAccess to fertility care support through Carrot, in addition to $4,000 reimbursement for related fertility expenses.\n\nAccess toWellhub, which connects employees to the best options for fitness, mindfulness, nutrition, and sleep in one subscription\n\nAccess to BrightHorizons, which provides sponsored child care, back-up care, and elder care\n\nUp to $1,000 Professional Development Reimbursement a year.\n\n$200 per year donation matching to support your favorite causes.\n\nNot sure if you meet every requirement? Research shows that women and people from historically underrepresented communities often hesitate to apply for roles unless they meet every qualification compared to other similarly-qualified candidates. At Spring Health, we are committed to fostering a workplace where everyone feels valued, empowered, and supported to Thrive. If this role excites you, we encourage you to apply.\nOur privacy policy: https://springhealth.com/privacy-policy/\nSpring Health is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex, marital status, ancestry, disability, genetic information, veteran status, gender identity or expression, sexual orientation, pregnancy, or other applicable legally protected characteristic. We also consider qualified applicants regardless of criminal histories, consistent with applicable legal requirements. Spring Health is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans. 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