3 months ago
Washington, DC, USAMid Level / Senior
Base Salary
$130k - $200k/yr
Responsibilities
- Design, train, evaluate, and deploy machine learning models across text, image, audio, and multimodal domains
- Develop classification systems for safety, security, abuse detection, and intelligence applications
- Benchmark, evaluate, and compare large language models and multimodal systems
- Contribute to model distillation, optimization, and fine-tuning efforts
- Design evaluation pipelines, metrics, and testing frameworks for model capabilities, reliability, and safety
- Build agentic systems and automated workflows for evaluation, red teaming, research, and large-scale experimentation
- Own ML projects from research and prototyping through production deployment and monitoring
- Partner with software engineers to productionize ML systems and support ongoing improvements
- Provide technical expertise across client engagements and internal research initiatives
Requirements
- 3–5+ years of professional experience building and deploying machine learning systems
- Strong proficiency in Python and modern machine learning frameworks such as PyTorch and/or TensorFlow
- Experience working across multiple modalities, with expertise in computer vision or natural language processing
- Experience training, fine-tuning, evaluating, and deploying machine learning models in production environments
- Experience designing evaluation methodologies, benchmarking systems, and model performance metrics
- Experience with MLOps tools and practices, including Docker, Kubernetes, CI/CD for ML, and MLflow
- Experience with cloud platforms such as Google Cloud Platform, AWS, or Azure, including ML infrastructure, workflow orchestration, storage, and database services
- Familiarity with model distillation, synthetic data generation, reinforcement learning, or AI evaluation research is strongly preferred
- Experience with frontier language models, multimodal foundation models, or AI safety evaluations is preferred
- Prior experience in cybersecurity, trust and safety, abuse prevention, threat intelligence, or related domains is preferred
- Experience with retrieval-augmented generation, AI agent frameworks, and context orchestration systems such as LangChain, LlamaIndex, OpenAI Agents, or AutoGen is preferred
Benefits
- Fully remote work for U.S.-based employees
- Comprehensive health, dental, and vision coverage
- Generous paid time off and paid holiday schedule
- Performance-based annual bonus
- Support for conferences, continuing education, or leadership training
Tech Stack
Categories
About 10a Labs
10a Labs is the safety and threat-intelligence layer trusted by frontier AI labs, AI unicorns, Fortune 10 companies, and leading global technology platforms. Our adversarial red teaming, model evaluations, and intelligence collection enable engineering, safety, and security teams to stay ahead of evolving threats and deploy AI systems safely.