Top AI & Machine Learning Jobs

Develop and apply mathematical, statistical, and computational methods to extract insights from large, messy NSA/CSS datasets. Design and implement machine learning and analytic models, perform data cleaning and management, communicate results to non‑technical stakeholders, and translate mission needs into technical requirements while accounting for classification and system constraints.

Lead design and hands-on development of scalable healthcare analytics, ML/AI, and data platform solutions. Architect SaaS cloud services, mentor engineers, align technical strategy with business needs, manage risk, and drive architectural innovation and stakeholder engagement.

Support HR&A Labs by performing geospatial and economic data analysis, building interactive dashboards and web tools, maintaining data systems, and contributing to client-facing deliverables. Work includes procuring/cleaning large datasets (census, PUMS), prototyping products with AI tools, and gradually owning analytics workstreams.

Build and maintain research automation and program-specific infrastructure for alignment research: orchestration, automated analysis, distributed training, experiment and evaluation systems; collaborate with researchers, contribute to shared codebases, and communicate progress across the organization.

Design and build agentic AI systems and LLM-based solutions for cybersecurity platforms. Implement ML/DL pipelines for threat detection, fine-tune and optimize models, create evaluation benchmarks, collaborate with security researchers and engineers, and deploy production-ready AI-driven SOC, SOAR, and SIEM workflows.

Evaluate and benchmark new LLM releases across legal, tax, coding, finance and other tasks. Analyze failure modes, maintain model integrations and benchmarking infrastructure, collaborate with research and communications teams, and publish leaderboard results used by startups, enterprises, and research labs.

Conduct research on agent behavior and systems solving identity, delegation, permissions, memory, provenance, and auditability. Move from papers and unclear questions to building code, experiments, prototypes, and deployable systems that demonstrate and validate solutions.

Lead launch and operations of NeuraGym US facility, manage on-site technical teams, own facility setup and customer experience, monitor performance and costs, develop scalable SOPs, and partner with product to improve processes and tooling for future launches.

Own end-to-end ML model lifecycle from EDA and feature engineering to production deployment and monitoring. Collaborate with cross-functional teams to identify modeling opportunities, evaluate performance and business impact, integrate new data sources, and ensure scalable, observable production systems.

Own and scale product areas of Overjet's Insurance AI platform, focusing on claims automation and backend/data-heavy workflows. Prioritize and execute across workstreams, translate insurer needs into requirements, partner with Engineering, Data, and ML teams, and iterate based on product performance, customer feedback, and operational impact.