Remote Senior GenAI Engineer — ML Platform & MLOps

Fractal; United States; Remote; USD 130,000 - 150,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

Life insurance

Disability insurance

401(k) plan

Paid holidays

Parental leave

PTO policy

Job summary

Fractal Analytics seeks a hands-on engineer to develop, deploy, and operate production AI/ML solutions, focusing on large language models (LLMs), retrieval‑augmented generation (RAG), and agents. The role combines applied AI engineering with backend service design, scalable model serving, and MLOps to deliver reliable, observable AI services.

The engineer will work with customer AI teams, applied scientists, architects, and platform teams to translate requirements into production solutions,

Qualifications

• Proven experience delivering and supporting AI/ML services in production across backend development, model serving, and deployment automation.
• Strong Python programming and software engineering skills with automated testing and source control.
• Experience designing backend APIs and distributed services with asynchronous processing and retries.
• Hands-on with LLMs, RAG, embeddings, retrieval, or agent workflows and evaluation of outputs.
• Experience with containers, orchestration, CI/CD, IaC, and at least one major cloud platform.

Responsibilities

• Design and implement ML and GenAI solutions for real-time and batch use cases.
• Build and maintain inference APIs and backend services with robust contracts and authentication.
• Implement request tracing, logs, and distributed tracing; ensure data protection.
• Develop scalable model serving with concurrency, autoscaling, and cost optimization.
• Automate build, test, deployment, and environment promotion through CI/CD and MLOps.

Skills

Python

Backend APIs

LLM

RAG

CI/CD

Distributed systems

Cloud platforms

MLOps

Monitoring

Logging

Tools

Containers

Kubernetes

CI/CD

Infrastructure as Code

Major cloud platforms

Job description

Fractal Analytics seeks a hands-on engineer to develop, deploy, and operate production AI/ML solutions, focusing on large language models (LLMs), retrieval‑augmented generation (RAG), and agents. The role combines applied AI engineering with backend service design, scalable model serving, and MLOps to deliver reliable, observable AI services.

The engineer will work with customer AI teams, applied scientists, architects, and platform teams to translate requirements into production solutions,