Applied ML Engineer — Shape Production AI & RL Models

Macroscope Inc.; San Francisco (CA); On-site; USD 170,000 - 280,000; Full time

Job summary

Macroscope Inc. is seeking a Senior Applied ML Engineer to advance our AI capabilities. You will own large parts of the model development lifecycle—from evaluation datasets and experiments to training and fine-tuning models, including RL, and analyzing results to guide product decisions.

You will collaborate with founders and engineering to deploy models into production, improve system reliability, and stay at the frontier of RL training techniques.

Qualifications

• 3+ years of experience in applied machine learning, AI, or related engineering roles.
• Experience building, training, fine-tuning, or evaluating modern ML models in production or research environments.
• Experience with reinforcement learning or reinforcement learning for LLMs (RLHF, RLAIF, PPO, DPO, or similar).
• Strong skills in dataset creation, curation, and evaluation, including benchmarks and labeling strategies.
• Experience designing and running rigorous experiments and using data to drive model improvements.
• Familiarity with LLMs and the open-source model ecosystem.
• Strong software engineering skills and building reliable ML pipelines and tooling.

Responsibilities

• Own large parts of the model development lifecycle: build and maintain evaluation datasets, design experiments, train and fine-tune models including RL where appropriate.
• Analyze results to drive product decisions and improve models.
• Research and stay up to date on RL training techniques.
• Collaborate with product and backend teams to integrate models into production.

Skills

Applied ML

Model training

Reinforcement learning

LLMs familiarity

Dataset creation

Experiment design

Software engineering

Golang

Tools

Golang

Job description

Macroscope Inc. is seeking a Senior Applied ML Engineer to advance our AI capabilities. You will own large parts of the model development lifecycle—from evaluation datasets and experiments to training and fine-tuning models, including RL, and analyzing results to guide product decisions.

You will collaborate with founders and engineering to deploy models into production, improve system reliability, and stay at the frontier of RL training techniques.