Client-Facing ML Deployment Engineer (Healthcare AI)

AKASA; San Francisco (CA); On-site; USD 150,000 - 170,000; Full time

Benefits offered by this job

Flexible PTO

Health insurance

HSA contributions

Parental leave

Life insurance

Home office stipend

Cell phone/internet reimbursement

Company-paid holidays

401(K) plan

Job summary

AKASA is deploying AI-native healthcare solutions and empowering revenue cycle teams. As Forward Deployed Engineer, you will lead client deployments, manage ML model lifecycles, and ensure reliable production operation.

You will collaborate with client engagement, product, and R&D teams to deliver scalable, robust deployment platforms and continuously improve model evaluation. Applicants should have strong Python and API/data skills.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or similar.
• 3+ years of professional Python experience.
• Experience designing and running LLM evals (offline and online).
• Comfortable with relational databases, APIs and ETL pipelines.
• Strong communication and interpersonal skills with meticulous attention to detail.

Responsibilities

• Execute deployments for client implementations from requirements to production rollout.
• Guide customers through onboarding, integration setup, troubleshooting, and data acquisition.
• Build and own evaluation frameworks to measure model quality across deployments.
• Collaborate with R&D and product teams to improve platform and tools.
• Work with client engagement teams to ensure smooth deployments and production stability.

Skills

Python

LLM evals

Relational DBs

APIs

ETL pipelines

Communication

Education

Bachelor's degree in Computer Science or Engineering

Tools

FastAPI

SQLAlchemy

Postgres

Docker

Kubernetes

AWS

GitHub Actions

Job description

AKASA is deploying AI-native healthcare solutions and empowering revenue cycle teams. As Forward Deployed Engineer, you will lead client deployments, manage ML model lifecycles, and ensure reliable production operation.

You will collaborate with client engagement, product, and R&D teams to deliver scalable, robust deployment platforms and continuously improve model evaluation. Applicants should have strong Python and API/data skills.