Data Scientist Agentic AI Systems Loops

We are seeking a Data Scientist with a strong research mindset to help shape the future of agentic AI systems. This role blends deep analytical thinking with fast-paced experimentation and model development where your insights will directly inform how AI agents reason plan and act in dynamic environments.

Youll work on a cross-functional team exploring how AI agents learn from real-world data adapt to user intent and interact autonomouslyor collaborativelywith users and systems. If youre a self-starter who thrives on ambiguity builds fast and can bridge theory with practical outcomes this role is for you.

Key Responsibilities

• Design and run applied research initiatives that inform the behavior and learning loops of AI agents
• Build and evaluate models for planning memory retrieval reasoning or tool use in agentic systems
• Develop internal tools and pipelines to test agent behavior across different environments
• Analyze structured and unstructured data from user-agent interactions logs and experiments
• Rapidly prototype and test hypotheses to improve agent performance and reliability
• Collaborate with engineering product and design to translate insights into deployable features
• Communicate findings clearly and concisely to both technical and non-technical audiences

Qualifications :

Minimum Qualifications

• Masters or PhD in Computer Science Applied Math Statistics or related quantitative field
• 4 years of experience in data science applied ML or AI research
• Strong Python and SQL skills; experience with libraries like scikit-learn PyTorch LangChain or any similar agentic framework
• Familiarity with LLMs retrieval-augmented generation (RAG) Reinforcement Learning Fine-Tuning
• Comfort with ambiguity fast iteration cycles and self-directed research
• Excellent communication and storytelling skills you can explain complex models to others clearly

Preferred Qualifications

• Experience working with agent frameworks (AutoGen OpenAgents LangGraph etc.)
• Background in decision-making models memory systems or multi-agent coordination
• Exposure to vector databases embeddings and custom RAG pipelines
• Experience building evaluation frameworks or simulators for agent performance
• Experience with LLM Post Training SFT DPO RLHF GRPO

Who You Are

• Curious  You explore the edges of whats possible with AI agents
• Action-biased  You ship prototypes quickly and iterate based on evidence
• Scientific  You bring structure to messy problems and back claims with data
• Independent  You operate autonomously and drive projects end-to-end
• Collaborative  You thrive in cross-functional teams and open discussion

Additional Information :

What Were Offering

• Salary Range: $140000 to $150000 annually bonus
• Flexible paid time off including sick and holiday
•  Medical dental & vision insurance
•  401K with Company contribution
•  Flexible spending accounts
•  Life insurance and disability benefits
•  Tuition assistance
•  Community involvement and volunteering events

M/F/Disabled/Vet VEVRAA Federal Contractor.  We are a Drug-Free Workplace. Interested candidates should apply at: qualified applicants will receive consideration for employment without regard to race color religion sex sexual orientation gender identity national origin disability or status as a protected veteran. VEVRAA Federal Contractor Equal Opportunity Employer

We embrace flexibility and hybrid work opportunities to support diverse needs and lifestyles while also valuing inclusive workplace experiences. By fostering a sense of community we drive innovation strengthen connections and nurture belonging. Our commitment ensures you can work in a way that suits you best while also engaging with colleagues to share ideas and build meaningful relationships.

All qualified applicants will receive consideration for employment without regard to race color religion sex sexual orientation gender identity national origin disability or status as a protected veteran. VEVRAA Federal Contractor Equal Opportunity Employer

Remote Work :

No

Employment Type :

Full-time