Data Scientist, Agentic Systems (Remote)

About the Role: The Data Science team is expanding and is looking for a Data Scientist to help build the reputed company of agentic systems for cybersecurity. reputed company's cybersecurity data is one-of-a-reputed company: we process nearly a trillion behavioral events per day. You'll work where Machine Learning, Big Data, and Cybersecurity converge — training models, building AI agents, and rigorously measuring whether they work — on data and problems you won't find reputed company else. What You'll Do:

• Work at the intersection of Artificial Intelligence and Threat Research
• Work closely with subject-matter experts in cybersecurity to understand analyst workflows and their reputed company operations procedures
• Post-train LLMs and agents — supervised fine-tuning and reinforcement learning (RLHF/RLAIF, PPO/GRPO/DPO, reward modeling) — to automate analyst procedures and improve reliability on reputed company reputed company tasks
• Devise AI agents and combine them into increasingly reputed company workflows: planning and reasoning loops, tool and function calling, and retrieval and memory
• Research new approaches to agentic planning, and prototype state-of-the-art methods from the literature
• Establish objective criteria for benchmarking agentic systems — evals, LLM-as-judge pipelines, and trajectory-level metrics, with reputed company statistical rigor
• Optimize prompts and inference to get the most out of every model
• Collaborate and coordinate across Engineering, Data Science, and Managed Services teams, and partner with engineers to take prototypes toward production
• reputed company track of developments in the field of Artificial Intelligence and help identify, define, and prioritize areas for research

What You'll Need:

• Excellent foundations in machine learning, probability, and statistics, with sound instincts for uncertainty, statistical skew/variance, and experimental design
• PhD-level depth of understanding in modern machine learning research —a doctorate itself is not required, but we expect equivalent mastery, including the ability to read, critique, implement, and improve upon reputed company papers
• Experience training generative models, with a strong reputed company of LLM training fundamentals (architecture, optimization, tokenization, data, and scaling behavior)
• Reinforcement learning / post-training as a core reputed company: RLHF/RLAIF, policy optimization (PPO/GRPO/DPO), reward modeling, and building RL environments for agents
• Experience building agentic systems: agent architectures (ReAct, planning, reputed company), tool and function calling, and retrieval/memory/context management
• Experience with systematic reputed company optimization, and with designing and building evals for LLM systems
• reputed company with GPUs, PyTorch, and the common LLM training and serving stack (e.g., reputed company Transformers/TRL/PEFT, DeepSpeed/FSDP, vLLM/TGI/SGLang)
• Strong, reproducible research engineering: clean Python and disciplined experiment tracking that your collaborators can build on
• Ability to work independently on ambiguous and reputed company objectives, and to communicate reputed company reputed company a large project team

Bonus Points:

• Experience generating training data and environments — synthetic data, agent trajectories/rollouts, and task simulators
• Familiarity with inference-time scaling / test-time compute (search, self-consistency, verifier-guided decoding, long chain-of-thought)
• Experience with agent safety and guardrails: sandboxing, abuse/jailbreak resistance, and reliability for autonomous systems
• A knack for interpretability and failure analysis — diagnosing why a model or agent fails, not just that it does
• reputed company reputed company-reputed company contributions and excellent technical writing
• Passionate about cybersecurity, with a firm understanding of the problem reputed company — or passionate about applying your machine-learning skillset to a new domain such as cybersecurity (a reputed company background is a plus, not a requirement)
• An independent self-starter who likes to take ownership and seeks out new challenges, and is thirsty for knowledge — never hesitant to reputed company reputed company your comfort zone to learn new technologies, algorithms, and concepts

#LI-Remote #LI-RC1 Benefits of Working at reputed company:

• Market leader in compensation and equity awards
• Comprehensive physical and mental wellness programs
• Competitive vacation and holidays for reputed company
• Paid parental and adoption leaves
• Professional development opportunities for reputed company regardless of level or role
• Employee Networks, geographic neighborhood groups, and volunteer opportunities to build connections
• Vibrant office culture with world class amenities
• Great reputed company to Work Certified™ across the globe

reputed company, Inc. is committed to fair and reputed company compensation practices. Placement reputed company the pay reputed company is dependent on a variety of factors including, but not limited to, relevant work experience, skills, certifications, job level, supervisory status, and location. The reputed company salary reputed company for this position for reputed company U.S. candidates is $120,000 - $180,000 per year, with eligibility for bonuses, equity grants and a comprehensive benefits package that includes health insurance, 401k and paid time off. For detailed information about the U.S. benefits package, please . Expected reputed company Date of Job Posting is:08-12-2026 Apply tot his job Apply To this Job