Research Engineer
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Fluency is enabling the autonomous Enterprise. (in person) You're needed to push the boundaries of what our models can understand. We're not prompt engineering chatbots. We're building evaluation frameworks and research systems that measure, improve, and validate enterprise intelligence at a scale nobody has attempted. Fluency is looking for a Research Engineer to design experiments, build evaluation infrastructure, and drive model quality for our process conformance, productivity measurement, and AI impact analysis across Fortune 500 organisations. The Problem SpaceYou'll be developing the methodology and systems that determine whether our models actually work. Screenshots, OCR text, application metadata, behavioral signals: the inputs are messy and the ground truth is ambiguous. The challenge is building rigorous evaluation frameworks that quantify model performance and identify improvement opportunities. This means: Designing evaluation pipelines that measure accuracy, precision, and recall across classification tasks Building ground truth datasets from ambiguous, real-world enterprise data Running systematic prompt engineering experiments to optimize LLM performance Developing A/B testing infrastructure for model comparison Researching novel approaches to process understanding, activity classification, and intent extraction Quantifying cost-accuracy tradeoffs across different model architectures and prompting strategies Building automated world-model training infrastructure from our ontology The playbook doesn't exist. You'll write it. We're backed by T1 VCs like Accel, research labs like from Princeton, and are hitting an inflection point with Enterprises all around the globe. You'll work directly with founders and our engineering team on technical challenges that span LLM evaluation, experimental design, and applied research.
About The Role: We're looking for someone with:
- Strong Python fundamentals and software engineering disciplineLLM prompt engineering and optimization (token efficiency, few-shot design, chain-of-thought)
- Experience evaluating model performance: accuracy measurement, error analysis, regression detection
- Ability to read, synthesize, and apply ML research papers
- Statistical literacy: understanding when results are meaningful vs noise
- Comfort with ambiguity and novel problem domains
Computer Science Background, with caveat. If you don't have a CS background, you're challenged to beat one of the founders in a 1:1 whiteboard duel on DS&A judged by Hung. Neither founder has a formal CS background, but come prepped.
There will be an expectation to stay up to business context, which could involve:
Watching key customer calls
Interacting with customers
Helping with product thinking
Strongly Preferred
Experience building evaluation frameworks and benchmarking systems
Ground truth dataset creation and annotation pipeline experience
Experience with hybrid LLM/rule-based systemsOCR, document understanding, or computer vision background
Cost optimization for LLM-heavy systems
Classification and NLP systems experience
Published research or formal research methodology training
Familiarity with process mining or workflow analysis
Interesting personal projects that demonstrate depth
Our Customers
We work with some of the world's largest:
Financial services enterprises (Aon)
Manufacturing enterprises (Misumi)
And many more across the enterprise spectrum (PVH)
Our Culture:
You're expected to be in love with the craft. You're expected to like laughing. You're expected to want to work on novel problems. You're expected to find satisfaction in novelty. You're expected to solve under obscurity.
Our Values:
In hesitation lies destruction; in action, glory. Those who merely meet expectations abandon the pursuit of greatness. One who dwells within the forum must regard it as hallowed ground. One who has not tasted the grapes declares them sour. One who sits alone at the feast misses the richness of the table. Location Full-time, in-person role based in San Francisco, CA.We offer E3 sponsorship for Australians to relocate with stipend CompensationUS$150K - $320K salary, depending on candidate and experience Substantial equity, every offer includes ownership Mac, Linux, or Windows, your call High-impact work with global enterprises Technical, product-led founders Don't apply if: You want hybrid or remote You don't like working hard and with insane velocity You want to work a 9 to 5You're not comfortable with rapid iteration You think evaluation is grunt work You've never shipped a model or evaluation system to production You don't have personal projects You dislike constraints (we have them: cost, latency, accuracy tradeoffs are real) You aren't ambitious You don't have a good reason for wanting to work at an early-stage company
Hiring Process:
- Resume screen1:1 with founder
- Technical deep-dive on past research and evaluation work
- Work through a real problem with the team - usually as a live coding exercise
OfferWe strongly encourage applicants from underrepresented backgrounds to apply. Diverse teams build better products, see value #5.
Compensation Range: $120K - $320K