Job description

Our mission: e liminating every barrier to mental health. Spring 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. Our 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. As 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. Reporting to the Senior Director, Engineering in Customer Value, this Staff Data Scientist will architect the critical semantic and intelligence layers required to make our profile data consumable for AI-native development and downstream product features. Please note that 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 Street location. Candidates must be based in the San Francisco metro 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 Take ownership of a team’s semantic and intelligence architecture—providing system-wide design guidance for profile data (member, customer, provider) and ensuring robust data contracts across platform teams. Use AI to explore and validate architectural patterns and decisions; design AI-augmented workflows (e.g., automated code generation, incident analysis) that multiply team output and enable engineers at all levels to work more effectively, specifically for personalized decisioning systems, agentic workflows, and real-time inference serving on AWS. Establish guardrails for safe and responsible AI usage across your team, covering security, compliance, and output correctness, specifically for LLM-based systems, ensuring compliance and correctness. Critically influence large, cross-team projects—ensuring execution without delay or compromise, and anticipating and removing barriers of all kinds. Bring critical thinking and drive shared understanding in ambiguous situations; given a clear vision, create a strategy; given a clear strategy, define a sequence of objectives, specifically for the core intelligence and recommendation engine. Develop strong working relationships cross-functionally and with business stakeholders; make sound tradeoffs between competing needs across short- and long-term horizons. Empower data scientists and engineers to set ambitious goals and turn vision into reality; mentor and develop engineers across the organization, not just your immediate team, mentoring on DS/ML best practices. Participate in an on-call rotation; push for better preparation and planning to reduce the frequency and impact of production incidents. What success looks like in this role Architectural Ownership – You are responsible for parts of our semantic layer and intelligence engine architecture. Your designs are exemplary—others reference them as the standard for engineering excellence across the org. AI-Augmented Engineering – You design workflows and tooling that make AI a force multiplier for your team, transitioning from rules-based heuristics to predictive ML and deep learning in the personalized decisioning layer and ensuring that the tools your team develops are usable in AI native flows. You establish guardrails that keep AI usage safe, compliant, and high-quality. Strategic Clarity – You turn vision into strategy and strategy into objectives. You bring structure and shared understanding to the most ambiguous problems on your team and across the org. You shape technical design and requirements, bringing together diverse stakeholder constraints. Cross-Org Influence – You drive best practices beyond your immediate team. Engineers and leaders across the organization seek your input on the hardest technical problems. People & Org Health – You empower others to do their best work—providing proper context, mentoring across levels, and fostering an inclusive, high-trust culture. Operational Reliability – You handle escalations reliably and lead high-stakes investigations with calm, clear communication. You drive systemic improvements to reduce future incidents. Engineering Excellence – You lead large-scale initiatives to reduce tech debt, improve architecture, and raise the quality bar, ensuring latency and scalability targets for production AI systems. You leave every system better than you found it. What you’ll bring 8+ years of experience building production ML/AI systems, inference microservices, and real-time data pipelines Hands-on experience with Snowflake and OpenSearch for profile data/vector search Experience with LLM orchestration (LangGraph, LangSmith) Proven track record at the Staff level of operating effectively in highly ambiguous territories, investigating emerging technologies, and aligning diverse stakeholders around a clear technical strategy Demonstrated ability to mentor and develop engineers across the organization Adept at covering the breadth of technology while diving deep into architectural complexity and scalability for data flows, model pipelines and inference endpoints and management Track record of technical leadership: creating clarity from ambiguity, defining strategy from vision, and driving org-wide architectural improvements Advanced degree (MS/PhD) in Computer Science, Machine Learning, or related field The target base salary range for this position is $239,000 - $270,000, 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. Not 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. Our privacy policy: springhealth.com Spring 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. If you have a disability or special need that requires accommodation, please let us know.

Requirements

Must-haves

Our mission: e liminating every barrier to mental health.
What you’ll do
Take ownership of a team’s semantic and intelligence architecture—providing system-wide design guidance for profile data (member, customer, provider) and ensuring robust data contracts across platform teams.
Establish guardrails for safe and responsible AI usage across your team, covering security, compliance, and output correctness, specifically for LLM-based systems, ensuring compliance and correctness.
Critically influence large, cross-team projects—ensuring execution without delay or compromise, and anticipating and removing barriers of all kinds.
Develop strong working relationships cross-functionally and with business stakeholders; make sound tradeoffs between competing needs across short- and long-term horizons.
Empower data scientists and engineers to set ambitious goals and turn vision into reality; mentor and develop engineers across the organization, not just your immediate team, mentoring on DS/ML best practices.
Participate in an on-call rotation; push for better preparation and planning to reduce the frequency and impact of production incidents.
What success looks like in this role
Cross-Org Influence – You drive best practices beyond your immediate team. Engineers and leaders across the organization seek your input on the hardest technical problems.
People & Org Health – You empower others to do their best work—providing proper context, mentoring across levels, and fostering an inclusive, high-trust culture.
Operational Reliability – You handle escalations reliably and lead high-stakes investigations with calm, clear communication. You drive systemic improvements to reduce future incidents.
What you’ll bring
8+ years of experience building production ML/AI systems, inference microservices, and real-time data pipelines
Hands-on experience with Snowflake and OpenSearch for profile data/vector search
Experience with LLM orchestration (LangGraph, LangSmith)
Proven track record at the Staff level of operating effectively in highly ambiguous territories, investigating emerging technologies, and aligning diverse stakeholders around a clear technical strategy
Demonstrated ability to mentor and develop engineers across the organization
Adept at covering the breadth of technology while diving deep into architectural complexity and scalability for data flows, model pipelines and inference endpoints and management
Track record of technical leadership: creating clarity from ambiguity, defining strategy from vision, and driving org-wide architectural improvements
Advanced degree (MS/PhD) in Computer Science, Machine Learning, or related field
A yearly allotment of no cost visits to the Spring Health network of therapists, coaches, and medication management providers for you and your dependents.
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.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aiawsllmmlmachine learning

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Paid Time Off

Parental Leave

Professional Development