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Senior AI Engineer, MLOps & Distributed Systems

Hinge HealthSan Francisco-HQRnD
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Salary
$164.8K – $247K
Job type
Full-time
Work mode
Remote
Posted
30 Sept 2026
Status
Open · checked 7d ago

About this role

Hinge Health is seeking a Senior AI Engineer, MLOps & Distributed Systems to join the team in San Francisco or remotely. This full-time role is ideal for an experienced software engineer with a strong background in distributed systems who wants to bridge the gap between machine learning models and reliable member experiences.

Role Overview

As a Senior AI Engineer focused on MLOps and distributed systems, the successful candidate will own the production path that turns models and artificial intelligence capabilities into dependable member-facing experiences. The Proactive Communications & Notifications pod creates the systems determining message delivery timing, channel selection, and relevance to help members stay engaged with care. This position focuses on designing and operating deployment, serving, release automation, monitoring, rollback, orchestration, and backend integration systems. The role collaborates closely with machine learning scientists, data scientists, data engineering, product teams, and software engineering.

Key Responsibilities

Build context on the member experience, communication systems, model lifecycle, data flows, and operational requirements within the first three months.
Establish service-level objectives, deployment paths, observability, and operational ownership for key AI-backed services.
Design and deliver production MLOps or distributed-systems initiatives from technical plans through rollout, measurement, and iteration.
Build and improve safe promotion patterns for model-backed services, including versioning, configuration, feature flags, canaries, rollback, and recovery.
Operate reliable online and batch inference capabilities that meet standards for latency, availability, correctness, resiliency, observability, and cost.
Create reusable patterns for APIs, services, queues, durable workflows, monitoring, and incident response.

Requirements

3+ years of non-internship, full-time professional software engineering experience.
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.

Nice to Have

Experience building or operating MLOps or machine learning platform capabilities like inference pipelines, model registries, or deployment automation.
Experience with online inference, batch scoring, recommendation systems, ranking, propensity models, or send-time optimization.
Familiarity with AWS and technologies such as Kubernetes, Docker, Kafka, PostgreSQL, Airflow, Databricks, or MLflow.
Experience with workflow orchestration and long-running state systems like Temporal, Step Functions, or Cadence.
Experience building observability for machine learning systems covering data quality, feature freshness, and prediction quality.
Experience partnering with machine learning scientists or data scientists without owning model training strategy.
Background in generative AI, large language models, retrieval systems, or model evaluation.
Experience in healthcare, digital health, fintech, or other regulated domains familiar with PHI, HIPAA, or privacy constraints.

Skills and Tools

Python
AWS
Kubernetes
Docker
TypeScript
JavaScript
Java
MLOps
Kafka
Airflow

Salary and Benefits

Annual salary range between $164,800 and $247,000 in USD.
Comprehensive medical, dental, and vision coverage, including gender-affirming care, family and fertility planning tools, and travel reimbursements.
Traditional or Roth 401(k) retirement plan options with a 2% company match.
Modern life stipends for continuous learning and development.
Employee Stock Purchase Plan (ESPP) with easy payroll deductions.

About the Company

Hinge Health uses technology to scale and automate the delivery of healthcare, beginning with musculoskeletal conditions that affect over 1.7 billion people globally. The platform offers an AI-powered, human-centered care model addressing acute injury, chronic pain, and post-surgical rehabilitation. Serving over 20 million people across more than 2,800 employers, Hinge Health is headquartered in San Francisco with additional offices in Montreal and Bangalore.

How to Apply

Interested candidates should visit the official Hinge Health careers page to submit an application.

Skills and tech stack

PythonLLMsKubernetesDockerAWSJavaTypeScriptJavaScriptMLOpsKafkaAirflowGenerative AIDistributed Systems

Questions candidates ask

What is the salary range for the Senior AI Engineer position?

The annual salary ranges from $164,800 to $247,000 USD.

Is this position remote?

Yes, this role offers remote flexibility while being headquartered out of San Francisco.

What level of experience is required?

Candidates must have a minimum of 3 years of non-internship, full-time professional software engineering experience, including designing and operating backend or distributed systems in production.

Do I need to train machine learning models in this role?

No, you do not need to be a research scientist or own model training strategy; your impact comes from making AI capabilities safe to ship and operate in production.

What programming languages are required?

Strong proficiency in Python is required, alongside experience with at least one production backend language such as TypeScript, JavaScript, Go, Java, or Kotlin.

Ready to apply?

The application is on the official Hinge Health careers page.

Apply on company site