Job Overview
Location
Palo Alto
Job Type
Full-time
Category
Data Science
Date Posted
May 8, 2026
Full Job Description
đź“‹ Description
- • Lead applied research and development for models and datasets at the core of Fiddler's Trust Service and suite of guardrail classifiers and evaluators that customers depend on to keep their LLM and agentic applications safe, accurate, and compliant in production.
- • Partner closely with engineering, Product, and Customer Success teams to build strong relationships with customer data science and ML engineering teams, supporting their AI observability journey and ensuring they realize measurable value from Fiddler.
- • Design, train, and ship production classifiers for safety, security, and quality detection (e.g., prompt injection, jailbreaks, PII, hallucination, faithfulness) under strict latency and cost constraints.
- • Lead the development of synthetic and adversarial dataset pipelines, including novel methods for generating, filtering, and validating data that exposes failure modes models need to learn.
- • Drive the technical direction of generative insights – the LLM- and agent-powered analysis layer that helps customers diagnose what's going wrong in their AI applications and why.
- • Contribute to the evaluation and experimentation infrastructure that lets the AI Science team and customers reliably measure model quality, regression, and drift across rapidly evolving model populations.
- • Explore reinforcement learning and preference-based methods where they offer real leverage over supervised baselines.
- • Collaborate with Backend and Platform engineers to take research prototypes from notebook to a hardened, scaled, observable service.
- • Mentor AI Scientists on the team, raise the technical bar through code review and design review, and represent Fiddler externally through publications, talks, or open-source contributions when appropriate.
🎯 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
- • Deep expertise training and fine-tuning classifier models, including modern encoder architectures (BERT-family, ModernBERT, etc.) and LLM-as-classifier approaches; clear understanding of the tradeoffs between them
- • Hands-on experience with dataset development as a first-class engineering discipline: sourcing, labeling, synthetic generation, adversarial augmentation, and quality control
- • Strong applied experience with LLMs and agentic systems – prompting, fine-tuning, and evaluation
- • Proficiency in Python and the modern ML stack (PyTorch, Hugging Face, common training/serving frameworks)
- • Comfortable working in production environments and partnering with backend and platform engineers on real-time inference, monitoring, and rollout
- • Excellent written and verbal communication; able to explain research tradeoffs to engineers, PMs, and customers
🏖️ Benefits
- • Unlimited PTO
- • Competitive pay + equity
- • Premium health, dental & vision (100% premiums covered for employee)
- • 401(k) plan
- • Monthly fitness reimbursement
- • Paid parental leave
- • Free annual Caltrain pass
- • Monthly in-office massages
- • Fastrak reimbursement
- • Free lunch Mon–Thurs
Skills & Technologies
About Fiddler Labs, Inc.
Fiddler Labs provides an enterprise platform for monitoring, explaining, and analyzing machine-learning models throughout their lifecycle. The software tracks data drift, bias, and performance anomalies, generating real-time alerts and detailed explanations to help data scientists, risk officers, and business users understand and trust AI decisions. Customers deploy Fiddler for compliance, governance, and continuous improvement of production models across financial services, healthcare, retail, and technology sectors.
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