Machine Learning Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Design and conduct machine learning experiments to assess the capabilities, behaviors, robustness, and constraints of cutting-edge AI systems.

• Create and assess models in areas such as reinforcement learning, natural language processing (NLP)/large language models (LLMs), computer vision, and multimodal machine learning.

• Construct evaluation pipelines, benchmarks, datasets, and metrics for next-generation AI systems.

• Train, fine-tune, and assess models for safety, security, and other high-impact applications.

• Develop dependable tools and infrastructure to execute machine learning experiments and evaluations on a large scale.

• Analyze outcomes, identify model failure modes, and convert insights into new experiments and technical strategies.

• Collaborate with engineers, analysts, red team members, and subject-matter experts to support leading AI organizations.

⛳️ Requirements

• 3–5+ years of experience in machine learning, research engineering, or a related technical domain.

• Proficient in Python with experience in machine learning frameworks such as PyTorch or JAX.

• Practical experience in training, fine-tuning, or evaluating contemporary machine learning models.

• Strong grasp of experimental design, model evaluation, and quantitative analysis.

• Familiarity with the fundamentals of agentic AI, including common harnesses, Model Context Protocol, agent benchmarks, and security risks associated with AI agents.

• Experience in one or more areas: reinforcement learning, NLP/LLMs, computer vision, or multimodal machine learning.

• Solid software engineering principles and the capability to work autonomously on complex technical challenges.

🏝️ Benefits

• Performance-based annual bonus.

• Support for conferences, continuing education, or leadership training.

• Fully remote, U.S.-based position.

• Comprehensive health, dental, and vision insurance.

• Generous paid time off (PTO) and paid holiday schedule.