Machine Learning Engineer

Role Overview

Machine Learning Engineer designing, building, evaluating, and deploying production-ready ML systems focused on AI safety, security, and intelligence. You’ll cover the full ML lifecycle and collaborate with interdisciplinary teams to advance research-driven engineering.

Responsibilities

• Design, train, evaluate, and deploy ML models for text, image, audio, and multimodal data.
• Build classification systems for safety, security, abuse detection, and intelligence.
• Run benchmarking and evaluation experiments for LLMs and multimodal models.
• Support model distillation, optimization, and fine-tuning for performance and deployability.
• Create evaluation pipelines, metrics, and testing frameworks to assess model capability and safety.
• Build agentic systems and automated workflows for evaluation, red teaming, research, and experimentation.
• Manage ML projects from research/prototyping through production deployment and monitoring.
• Collaborate with software engineers to productionize ML systems and iterate on improvements.
• Provide technical expertise across client projects and internal research initiatives.

Requirements

• 3 to 5+ years of experience building and deploying ML systems.
• Proficiency in Python with PyTorch and/or TensorFlow.
• Strong experience with multiple modalities, with expertise in computer vision and/or natural language processing.
• Proven experience training, fine-tuning, evaluating, and deploying models in production.
• Ability to design evaluation methodologies, benchmarking systems, and performance metrics.
• MLOps familiarity including Docker, Kubernetes, CI/CD, and MLflow.
• Cloud experience with GCP (preferred), AWS, or Azure.

Nice to Have

• Model distillation, synthetic data generation, reinforcement learning, or AI evaluation research.
• Experience with frontier language models, cybersecurity, trust & safety, or retrieval-augmented generation (RAG) frameworks.

Compensation & Work Setup

• $130,000–$200,000 salary range (based on experience and location)
• Performance-based annual bonus
• Fully remote for U.S.-based employees
• Health/dental/vision coverage, paid time off, professional development support