Machine Learning Engineer

Second Talent; United States; Remote; USD 140.000 - 230.000; Vollzeit

Zusammenfassung

Second Talent is recruiting an experienced Machine Learning Engineer to join the Environments team. The role centers on building simulation environments for AI coding agents to learn and refine machine learning strategies, while delivering robust testing infrastructure over large-scale ML codebases.

You will create end-to-end tests for RL frameworks, reproduce results from papers in PyTorch or Jax, and automate task and test generation to accelerate development.

Qualifikationen

• Experience with ML frameworks like PyTorch or Jax and deep hands-on work with ML models.
• Proven track record of training large models on large datasets in multi-GPU environments.
• Ability to learn new technologies and complex codebases rapidly.

Aufgaben

• Write an end-to-end test for a Reinforcement Learning framework to ensure reward function progresses or to detect numerical instabilities.
• Implement research-proposed algorithms (in PyTorch or Jax) and develop a comprehensive test suite to evaluate AI agent performance.
• Build automation tooling to speed up creation of new ML tasks and testing pipelines.

Kenntnisse

Python

ML frameworks

Reinforcement Learning

Multi-GPU training

Testing infrastructure

Tools

PyTorch

Jax

Jobbeschreibung

Our client, a leading AI research company, is seeking an experiencedMachine Learning Engineer to join their "Environments" team. This is a critical infrastructure role focused on building the "simulation environments" where their advancedAI coding agents learn to become proficient in real-worldMachine Learning engineering.

You will be responsible for building complextesting infrastructure on top of large-scale, third-party ML codebases. Your work will "grade" the AI agent's solutions on difficult tasks, such as implementing algorithms from research papers or debugging training frameworks. You will also build automations to accelerate the testing and task-creation process.

This role requires an engineer who can dive into new, unfamiliar, and highly complex ML codebases and frameworks with exceptional speed.

Example Responsibilities

• Write anend-to-end test for aReinforcement Learning (RL) framework to ensure that a small model's reward function is increasing as expected or to detectnumerical instabilities.
• Findresearch papers proposing algorithmic improvements for model training, implement them (inPyTorchorJax), and then write an extensive test suite to evaluate whether an AI agent can successfully reimplement those same algorithms.
• Build automation tooling to speed up the creation of new ML tasks and testing pipelines.

Required Qualifications

• Experience:Must have multiple years of deep, hands‑on experience working withMLframeworks likePyTorchorJax.
• Track Record:A demonstrable track record oftraining large modelsonlarge datasetsusinglarge-scale, multi-GPUenvironments.
• Key Attribute:A proven, exceptional ability tolearn new technologies and complex codebasesat a very fast pace.
• Engineering Skills:Strong software engineering fundamentals, particularly inPython, and the ability to build robust, maintainable testing infrastructure.

Interview Process

The interview process is designed to be fast and decisive. It typically consists of 2-3 technical interviews, with a final decision and offer made withinseven days in most cases.