Applied ML Engineer: RL Fine-Tuning for LLM Agents

Jack & Jill; San Francisco (CA); On-site; USD 170,000 - 280,000; Full time

Benefits offered by this job

Equity 0.25%-0.5%

Job summary

Macroscope, a San Francisco-based startup, is hiring an Applied ML Engineer to own the ML lifecycle for our agent-powered development infrastructure. You will focus on training and fine-tuning LLMs using advanced reinforcement learning techniques and build evaluation datasets to drive model improvements.

You'll work with backend engineers on production integration using Golang, Temporal, and AST code walkers, contributing to core infrastructure and code-quality tooling.

Qualifications

• 3+ years of applied ML experience in production or research.
• Hands-on RL for LLMs (RLHF, DPO, GRPO) with training dynamics.
• Strong software engineering skills and reliable ML pipelines.

Responsibilities

• Train and fine-tune LLMs using RL methods to improve code generation.
• Design datasets and benchmarks to measure model performance.
• Collaborate with engineers to deploy models into production.

Skills

Applied ML

RL for LLMs

Software pipelines

Golang

Temporal

AST code walkers

Tools

Golang

Temporal

AST code walkers

Job description

Macroscope, a San Francisco-based startup, is hiring an Applied ML Engineer to own the ML lifecycle for our agent-powered development infrastructure. You will focus on training and fine-tuning LLMs using advanced reinforcement learning techniques and build evaluation datasets to drive model improvements.

You'll work with backend engineers on production integration using Golang, Temporal, and AST code walkers, contributing to core infrastructure and code-quality tooling.