MLOps / AI Platform Engineer

Tala Health; San Francisco (CA); On-site; USD 140,000 - 200,000; Full time

Job summary

Tala Health in San Francisco is seeking an experienced MLOps/AI Platform Engineer to own the end-to-end ML infrastructure, from model submission to bedside delivery.

You will design CI/CD for data, model, and code; maintain registries and experiment tracking; and ensure HIPAA compliance while keeping uptime high and costs in check.

Qualifications

• 5+ years DevOps/backend experience, with 2+ years ML/data-platform work.
• Deep comfort with AWS (or GCP/Azure), Terraform, Docker and Kubernetes.
• Hands-on with workflow schedulers (Airflow, Prefect) and message/queue systems.
• Proven track record building monitoring/alerting stacks (Prometheus, Grafana, Loki, ELK).
• Strong Python skills; Go or TypeScript familiarity welcome.
• Understanding of data‑privacy/compliance in regulated industries.

Responsibilities

• Design CI/CD flows for data, model and code; automate testing and rollout with GitHubActions or Argo.
• Stand up and manage a feature store, model registry and experiment-tracking stack (MLflow, W&B, Kubeflow).
• Containerize and serve models via Triton, TorchServe or custom FastAPI micro-services on Kubernetes.
• Build observability for drift, latency and cost; trigger retraining or rollback when thresholds trip.
• Implement zero-trust security, audit logging and encryption to satisfy SOC2 & HIPAA.
• Provide self-service tools and docs so Data Scientists can deploy without ticket queues.

Skills

DevOps

Backend

ML platform

Python

Go/TS

Compliance

AWS

Terraform

Docker

Kubernetes

Airflow

Prefect

Monitoring

Prometheus

Grafana

MLflow

W&B

Kubeflow

Triton

TorchServe

FastAPI

GitHub Actions

Argo

Tools

MLflow

W&B

Kubeflow

Triton

TorchServe

FastAPI

GitHub Actions

Argo

Terraform

Job description

Back to Careers

Oct 1, 2025

San Francisco, California, United States

MLOps / AI Platform Engineer

About Us

Tala Health was built to transform a healthcare system that remains slow, expensive and inefficient. Today’s patients often face a fragmented system that requires juggling doctor visits, lab work, referrals and long wait times just to reach a diagnosis. With Tala Health, patients will receive a new kind of care experience that brings AI agents and clinicians together from the start to deliver accurate, personalized care faster. We are building AI agents to support the full arc of the patient journey.

The Opportunity: MLOps / AI Platform Engineer

Own the engine that moves models from laptop to bedside. You’ll architect the pipelines, registries and monitoring that let researchers ship safely, quickly and compliantly, keeping one eye on uptime and the other on HIPAA.

What You’ll Do

• Design CI/CD flows for data, model and code; automate testing and rollout with GitHubActions or Argo.
• Stand up and manage a feature store, model registry and experiment‑tracking stack (MLflow, W&B, Kubeflow).
• Containerize and serve models via Triton, TorchServe or custom FastAPI micro‑services on Kubernetes.
• Build observability for drift, latency and cost; trigger retraining or rollback when thresholds trip.
• Implement zero‑trust security, audit logging and encryption to satisfy SOC2 & HIPAA.
• Provide self‑service tools and docs so Data Scientists can deploy without ticket queues.

What You Bring

• 5+years DevOps / backend experience, with 2+years focused on ML or data‑platform work.
• Deep comfort with AWS (or GCP/Azure), Terraform, Docker and Kubernetes (GPU orchestration a plus).
• Hands‑on experience with workflow schedulers (Airflow, Prefect) and message/queue systems.
• Proven track record building monitoring/alerting stacks (Prometheus, Grafana, Loki, ELK).
• Strong Python skills; Go or TypeScript familiarity welcome.
• Understanding of data‑privacy and compliance requirements in regulated industries.