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Hinge Health

Runs virtual care for joint and muscle pain

Senior AI Engineer - Proactive Comms

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA

About the Job

Requirements

  • At least 3 years of non-internship, full-time professional software engineering experience.
  • At least 3 years designing, building, and operating backend or distributed systems in production, including participation in on-call and incident response.
  • Demonstrated experience deploying and operating machine-learning- or AI-backed services in production.
  • Strong proficiency in Python and at least one production backend language such as TypeScript/JavaScript, Go, Java, or Kotlin.
  • Experience building or operating MLOps or ML platform capabilities, such as inference pipelines, model registries, deployment automation, monitoring, evaluation integration, or automated retraining.
  • Experience with online inference, batch scoring, recommendation systems, ranking, propensity models, or send-time optimization.
  • Experience with AWS and production technologies such as Kubernetes, Docker, Kafka, PostgreSQL, Airflow, Databricks, MLflow, or equivalent systems.
  • Experience with workflow orchestration and long-running state, including Temporal, Step Functions, Cadence, or a comparable system.
  • Experience building observability for ML systems, including data quality, feature freshness, model behavior, prediction quality, latency, errors, and cost.
  • Experience partnering with ML Scientists or Data Scientists to define production interfaces and operate models without owning model research or training.
  • Experience integrating generative AI, large language models, retrieval, agents, or model evaluation into production products.
  • Experience in healthcare, digital health, fintech, or another regulated or data-sensitive domain; familiarity with protected health information, HIPAA, or comparable privacy constraints.

Responsibilities

  • Build context on the member experience, communication systems, model lifecycle, data flows, and operational requirements.
  • Establish a baseline for key AI-backed services, including service-level objectives, deployment paths, observability, failure modes, and operational ownership.
  • Deliver targeted improvements to developer experience, testing, release safety, or incident response.
  • Own the design and delivery of a production MLOps or distributed-systems initiative from technical plan through rollout, measurement, and iteration.
  • Build or improve safe promotion patterns for model-backed services, including versioning, configuration, feature flags, canaries, rollback, and recovery.
  • Partner with ML Scientists and Data Engineering to define durable interfaces, data contracts, feature inputs, freshness expectations, evaluation hooks, and production-readiness criteria.
  • Operate reliable online and batch inference capabilities that meet contracts for latency, availability, correctness, resiliency, observability, and cost.
  • Create reusable patterns for APIs, services, queues, durable workflows, monitoring, and incident response to support AI integration into notifications, personalization, send-time optimization, and related experiences.
  • Shape technical decisions, mentor engineers, raise quality through design and code review, and connect system reliability to member outcomes.
  • Own systems across architecture, implementation, launch, and operations, including on-call, incident response, debugging, root-cause analysis, and preventing recurring failures.
  • Write technical proposals, make risks and decisions visible, and explain system behavior to technical and non-technical partners.
  • Improve the team’s engineering workflow through reusable patterns, code reviews, pairing, and mentoring.
  • Safeguard privacy, security, auditability, and sensitive healthcare data.

About the Company

Hinge Health

Runs virtual care for joint and muscle pain

Hinge Health runs virtual care programs for joint and muscle pain, with employers and health plans buying access for eligible members. Its app combines personalized exercise therapy with licensed physical therapists, health coaches, and orthopedic specialists. Members use phone-based motion tracking for feedback on their exercises and communicate with their care team between sessions. Programs cover chronic pain, acute injuries, and rehabilitation after surgery, while clients pay for member subscriptions through direct contracts or health plan partners. Hinge Health was founded in 2014 and is headquartered in San Francisco, California, United States.

Company size
1,001-5,000
Company stage
IPO
Headquarters
San Francisco, CA
Founded
2014

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