Machine Learning Engineer

🔥 15 hours ago

🇺🇸 United States – Remote

💵 $130k - $200k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 19%

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Logo of 10a Labs

10a Labs

11 - 50 employees

Founded 2021

🤖 Artificial Intelligence

🔒 Cybersecurity

☁️ SaaS

Artificial Intelligence • Cybersecurity • SaaS

10a Labs is an applied research and technology company specializing in AI security. It delivers intelligence collection, investigative research, and analysis for AI unicorns, Fortune 10 companies, and U. S. tech leaders. The company provides services that empower security teams and technology leaders to stay ahead of evolving threats, drive innovation, and protect their brands. Their work includes stress-testing AI models against threats, developing real-time threat detection systems, and monitoring cyber threats to enhance AI safety and security throughout the product development lifecycle.

📋 Description

• Design and run ML experiments to evaluate the capabilities, behavior, robustness, and limitations of advanced AI systems • Develop and evaluate models across reinforcement learning, NLP/LLMs, computer vision, and multimodal ML • Build evaluation pipelines, benchmarks, datasets, and metrics for frontier AI systems • Train, fine-tune, and evaluate models for safety, security, and other high-impact applications • Develop reliable tooling and infrastructure to run ML experiments and evaluations at scale • Analyze results, identify model failure modes, and translate findings into new experiments and technical approaches • Collaborate with engineers, analysts, red teamers, and subject-matter experts supporting leading AI organizations

🎯 Requirements

• 3–5+ years of experience in machine learning, research engineering, or a related technical field • Strong Python skills and experience with ML frameworks such as PyTorch or JAX • Hands-on experience training, fine-tuning, or evaluating modern ML models • Strong understanding of experimental design, model evaluation, and quantitative analysis • Familiarity with agentic AI fundamentals, including common harnesses, Model Context Protocol, agent benchmarks, and security risks to AI agents • Experience in one or more of: reinforcement learning, NLP/LLMs, computer vision, or multimodal ML • Strong software engineering fundamentals and ability to work independently on ambiguous technical problems

🏖️ Benefits

• Performance-based annual bonus • Support for conferences, continuing education, or leadership training • Fully remote, U.S.-based • Comprehensive health, dental, and vision coverage • Generous PTO and paid holiday schedule

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