AI Research Scientist

This is a fully remote position, open to applicants in United States.

📋 Description

• Engage at the intersection of Artificial Intelligence and Threat Research.

• Collaborate closely with cybersecurity subject-matter experts to gain insights into analyst workflows and security operations protocols.

• Conduct post-training of LLMs and agents utilizing supervised fine-tuning, reinforcement learning, policy optimization, and reward modeling techniques.

• Develop AI agents and integrate them into progressively intricate workflows that encompass planning, reasoning, tool and function invocation, retrieval, and memory management.

• Investigate innovative methodologies for agentic planning and prototype leading-edge techniques sourced from current literature.

• Set objective benchmarking standards for agentic systems, including evaluations, LLM-as-judge pipelines, and trajectory-level metrics.

• Enhance prompts and inference to improve model performance.

• Collaborate with Engineering, Data Science, and Managed Services teams.

• Work alongside engineers to transition prototypes into production-ready solutions.

• Monitor advancements in artificial intelligence, identifying, defining, and prioritizing research opportunities.

⛳️ Requirements

• Strong foundation in machine learning, probability, and statistics.

• PhD-level expertise in contemporary machine learning research; a doctorate is not mandatory if equivalent proficiency is shown.

• Background in training generative models with a robust understanding of LLM training principles.

• Expertise in reinforcement learning and post-training techniques, including RLHF/RLAIF, PPO/GRPO/DPO, reward modeling, and RL environments.

• Experience in building agentic systems, covering ReAct, planning, reflection, tool and function invocation, retrieval, memory, and context management.

• Proficiency in systematic prompt optimization and the design and development of LLM evaluations.

• Familiarity with GPUs, PyTorch, and LLM training and serving frameworks such as Hugging Face Transformers/TRL/PEFT, DeepSpeed/FSDP, and vLLM/TGI/SGLang.

• Strong reproducible research engineering capabilities with clean Python code and disciplined experiment tracking.

• Ability to independently navigate ambiguous and complex objectives while communicating effectively within a large project team.

• Demonstrated experience leveraging AI technologies to enhance decision-making, streamline workflows, improve efficiency, and drive business results.

• Bonus: familiarity with synthetic data, agent trajectories/rollouts, task simulators, inference-time scaling, agent safety and guardrails, interpretability, failure analysis, open-source contributions, and technical writing.

• A passion for cybersecurity or the application of machine learning skills within the cybersecurity domain; a security background is advantageous but not a requirement.

🏝️ Benefits

• Competitive compensation and equity awards, leading the market.

• Comprehensive programs for physical and mental wellness.

• Generous vacation and holiday policies to promote rest and recharge.

• Paid parental and adoption leave benefits.

• Opportunities for professional development accessible to all employees, regardless of their role or level.

• Employee Networks, local community groups, and volunteer opportunities to foster connections.

• A vibrant office culture featuring world-class amenities.

• Health insurance coverage.

• 401k retirement plan.

• Paid time off.

• Performance bonuses.

• Equity grants.

• A comprehensive benefits package.