Machine Learning Engineer

1. About Our Client:

10a Labs operates in the AI safety and threat-intelligence sector, providing services to frontier AI labs, AI unicorns, Fortune 10 companies, and leading global technology platforms. The organization addresses challenges in AI safety and security by delivering adversarial red teaming, model evaluations, and intelligence collection, helping engineering, safety, and security teams anticipate and mitigate evolving threats to enable safe AI system deployment.

2. About the Opportunity:

The Machine Learning Engineer role involves designing, building, evaluating, and deploying advanced machine learning systems focused on safety, security, and intelligence applications. This position covers the full machine learning lifecycle and requires collaboration across interdisciplinary teams to develop production-ready systems that support leading AI organizations. The role contributes directly to advancing AI safety and security through research-driven engineering.

3. Responsibilities:

• • Design, train, evaluate, and deploy machine learning models for text, image, audio, and multimodal data.
• • Develop classification systems targeting safety, security, abuse detection, and intelligence.
• • Conduct benchmarking and evaluation experiments on AI models, including large language and multimodal models.
• • Contribute to model distillation, optimization, and fine-tuning to enhance performance and deployability.
• • Design evaluation pipelines, metrics, and testing frameworks to assess model capabilities and safety.
• • Build agentic systems and automated workflows for evaluation, red teaming, research, and experimentation.
• • Manage ML projects from research and prototyping to production deployment and monitoring.
• • Collaborate with software engineers to productionize ML systems and support ongoing improvements.
• • Provide technical expertise across client projects and internal research initiatives.

4. Requirements:

• • 3 to 5+ years of professional experience building and deploying machine learning systems.
• • Proficiency in Python and machine learning frameworks such as PyTorch and/or TensorFlow.
• • Experience with multiple modalities, with expertise in computer vision or natural language processing.
• • Experience training, fine-tuning, evaluating, and deploying ML models in production.
• • Ability to design evaluation methodologies, benchmarking systems, and performance metrics.
• • Familiarity with MLOps tools and practices including Docker, Kubernetes, CI/CD, MLflow.
• • Experience with cloud platforms such as Google Cloud Platform (preferred), AWS, or Azure.
• • Preferred experience with model distillation, synthetic data generation, reinforcement learning, or AI evaluation research.
• • Additional preferred experience includes work with frontier language models, cybersecurity, trust and safety, or retrieval-augmented generation frameworks.

5. Pay Range and Compensation Package:

• • Salary Range: $130,000 to $200,000, depending on experience and location.
• • Performance-based annual bonus.
• • Support for professional development including conferences, continuing education, and leadership training.
• • Fully remote work environment for U.S.-based employees.
• • Comprehensive health, dental, and vision coverage.
• • Generous paid time off and paid holiday schedule.

6. Benefits & Perks:

• • Comprehensive health insurance.
• • Dental insurance.
• • Vision insurance.

Equal Opportunity Statement: Our client is an equal opportunity employer. They celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, or national origin.

Note:

RemoteHunter is not the Employer of Record (EOR) for this role. Our purpose in this opportunity is to connect exceptional candidates with leading employers. We help job seekers worldwide discover roles that match their goals and guide them to complete their full application directly through the hiring company’s career page or ATS.