AI Scientist
Listed on 2026-07-15
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IT/Tech
AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Our Purpose
At Fiddler, we understand the implications of AI and the impact that it has on human lives. Our company was born with the mission of building trust into AI. The rise of Generative AI and Agents has unlocked generalized intelligence but also widened the risk aperture and made it harder to ensure that AI applications are working well. Fiddler enables organizations to get ahead of these issues by helping deploy trustworthy, and transparent AI solutions.
Fiddler partners with AI-first organizations to help build a long‑term framework for responsible AI practices, which, in turn, builds trust with their user base. AI Engineers, Data Science, and business teams use Fiddler AI to monitor, evaluate, secure, analyze, and improve their AI solutions to drive better outcomes. Our platform enables engineering teams and business stakeholders alike to understand the "what", “why”, and "how" behind AI outcomes.
Our Founders
Fiddler AI is founded by Krishna Gade (engineering leader at Facebook, Pinterest, Twitter, and Microsoft) and Amit Paka (product leader at Microsoft, Samsung, Paypal and two‑time founder). We are backed by Insight Partners, Lightspeed Venture Partners, and Lux Capital.
Why Join Us
Our team is motivated to help build trust into AI to enable society harness the power of AI. Joining us means you get to make an impact by ensuring that AI applications at production scale across industries have operational transparency and security. We are an early‑stage startup and have a rapidly growing team of intelligent and empathetic doers, thinkers, creators, builders, and everyone in between.
The AI and ML industry has a rapid pace of innovation and the learning opportunities here are monumental. This is your chance to be a trailblazer.
Fiddler is recognized as a pioneer in the field of AI Observability and has received numerous accolades, including: 2022 a16z Data
50 list, 2021 CB Insights AI 100 most promising startups, 2020 WEF Technology Pioneer, 2020 Forbes AI 50 most promising startups of 2020, and a 2019 Gartner Cool Vendor in Enterprise AI Governance and Ethical Response. By joining our brilliant (at least we think so) team, you will help pave the way in the AI Observability space.
You’ll join a tight‑knit, highly collaborative AI Science team that partners closely with some of the world’s leading enterprise AI organizations. We operate in a hybrid capacity, but stay deeply connected through constant communication, collaboration, and shared purpose. Our team thrives on knowledge sharing, peer learning, and collective problem solving – no one works in a silo.
We celebrate each other’s successes, support one another through complex challenges, and take pride in helping our customers achieve real‑world impact with Fiddler’s AI Observability platform. Every project is a team effort, and every win is shared. If you love working alongside smart, driven peers who genuinely care about both customer success and each other’s growth, you’ll feel right at home here.
What You’ll Do:Lead applied research and development. Lead applied research and development for the 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 other engineering teams, Product, and Customer Success. You’ll 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 our 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…
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