Staff AI Scientist

About the role

Fiddler is an AI observability platform that helps organizations build trustworthy AI solutions. Founded by Krishna Gade and Amit Paka, Fiddler is backed by leading venture capital firms and has received recognition for its pioneering work in AI governance and ethical response.

Responsibilities

• Lead applied research and development for models and datasets critical to Fiddler's Trust Service and suite of guardrail classifiers and evaluators.
• Partner closely with other engineering teams, Product, and Customer Success to support AI observability journeys and ensure customer value realization.
• Design, train, and ship production classifiers for safety, security, and quality detection.
• Develop synthetic and adversarial dataset pipelines, including novel methods for exposing failure modes.
• Drive the technical direction of generative insights and evaluation infrastructure.
• Collaborate with Backend and Platform engineers to take research prototypes to production.
• Translate enterprise customer needs into research problems and translate research results into product.
• Mentor AI Scientists and contribute to the technical community through publications, talks, or open-source contributions.

Requirements

• 7+ years of applied AI experience, with a strong track record of taking models from research to production.
• Experience in LLM or Agentic Evals, Guardrailing.
• Expertise in training and fine-tuning classifier models, including modern encoder architectures and LLM-as-classifier approaches.
• Strong applied experience with LLMs and agentic systems.
• Proficiency in Python and the modern ML stack (PyTorch, Hugging Face, common training/serving frameworks).
• Experience working in production environments and collaborating with backend and platform engineers on real-time inference, monitoring, and rollout.
• Excellent written and verbal communication skills, able to explain research tradeoffs to engineers, PMs, and customers.

Qualifications

• M.S. or Ph.D. in Computer Science, Machine Learning, Statistics, Physics, or a related quantitative field.
• Published research at top ML or NLP venues (NeurIPS, ICML, ICLR, ACL, EMNLP, etc.).
• Experience with reinforcement learning, RLHF, RLAIF, or preference-based fine-tuning.
• Background in AI safety, red-teaming, or adversarial ML.
• Experience working with enterprise customers in regulated industries (finance, healthcare, government).

Skills

• Expertise in training and fine-tuning classifier models.
• Strong applied experience with LLMs and agentic systems.
• Experience with dataset development as a first-class engineering discipline.
• Experience with reinforcement learning and preference-based methods.
• Experience with synthetic data generation pipelines at scale.

Benefits

• Competitive pay + equity
• Premium health, dental & vision (100% premium coverage for employees)
• 401(k) plan
• Open PTO
• Monthly fitness reimbursement
• Paid parental leave
• Team and company events and offsites
• Fully stocked snacks and drinks

Pay

• For Bay Area, Seattle & New York City: $220,000 - $260,000 + equity & benefits
• Other cities: $175,000-$230,000 + equity & benefits

Schedule

• The position offers flexibility with 2-3 days per week in the Palo Alto office.