Getfluency
Fluency is enabling the autonomous Enterprise.
You're needed to build the intelligence layer that understands how work actually happens. We're not fine-tuning chatbots. We're building systems that comprehend, classify, and quantify enterprise workflows at a scale nobody has attempted.
Fluency is looking for an ML/AI Engineer to design and build the models that power process conformance, productivity measurement, and AI impact analysis across Fortune 500 organisations.
The Problem Space You'll be building hybrid ML systems that operate on messy, real-world data: screenshots, OCR text, application metadata, and behavioural signals. The challenge is extracting structured understanding from unstructured chaos, at scale, with cost constraints that make brute-force LLM calls untenable.
This means:
Designing classification systems that detect AI tool usage across thousands of applications
Building process conformance models that compare observed workflows against ideal templates
Creating attribution models that quantify productivity impact with statistical rigour
Optimising inference pipelines to balance accuracy against token economics
The playbook doesn't exist. You'll write it.
We're backed by T1 VCs like Accel 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 classical ML, LLM orchestration, and production systems engineering.
About the Role We're looking for someone with:
Strong Python fundamentals and software engineering discipline
Experience building classification and NLP systems
LLM prompt engineering and optimisation (token efficiency, few-shot design, chain-of-thought)
Evaluation methodology: building ground truth datasets, A/B testing, accuracy measurement
Production ML experience: model serving, latency optimisation, monitoring
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 founders have 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 with hybrid ML/rule-based systems
OCR, document understanding, or computer vision background
Cost optimisation for LLM-heavy systems
PyTorch or similar framework experience
Familiarity with process mining or workflow analysis
You've shipped ML systems that operate at scale under real constraints
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
Compensation
US$150K - $250K 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 5
You're not comfortable with rapid iteration
You think prompt engineering is beneath you
You've never shipped a model to production
You dont have personal projects
You dislike constraints (we have them: cost, latency, accuracy tradeoffs are real)
You aren't ambitious
Hiring Process
Resume screen
1:1 with founder
Technical deep-dive on past ML work
Work through a real problem with the team
Offer
We strongly encourage applicants from underrepresented backgrounds to apply. Diverse teams build better products - see value #5.
#J-18808-Ljbffr
Fluency is looking for an ML/AI Engineer to design and build the models that power process conformance, productivity measurement, and AI impact analysis across Fortune 500 organisations.
The Problem Space You'll be building hybrid ML systems that operate on messy, real-world data: screenshots, OCR text, application metadata, and behavioural signals. The challenge is extracting structured understanding from unstructured chaos, at scale, with cost constraints that make brute-force LLM calls untenable.
This means:
Designing classification systems that detect AI tool usage across thousands of applications
Building process conformance models that compare observed workflows against ideal templates
Creating attribution models that quantify productivity impact with statistical rigour
Optimising inference pipelines to balance accuracy against token economics
The playbook doesn't exist. You'll write it.
We're backed by T1 VCs like Accel 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 classical ML, LLM orchestration, and production systems engineering.
About the Role We're looking for someone with:
Strong Python fundamentals and software engineering discipline
Experience building classification and NLP systems
LLM prompt engineering and optimisation (token efficiency, few-shot design, chain-of-thought)
Evaluation methodology: building ground truth datasets, A/B testing, accuracy measurement
Production ML experience: model serving, latency optimisation, monitoring
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 founders have 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 with hybrid ML/rule-based systems
OCR, document understanding, or computer vision background
Cost optimisation for LLM-heavy systems
PyTorch or similar framework experience
Familiarity with process mining or workflow analysis
You've shipped ML systems that operate at scale under real constraints
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
Compensation
US$150K - $250K 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 5
You're not comfortable with rapid iteration
You think prompt engineering is beneath you
You've never shipped a model to production
You dont have personal projects
You dislike constraints (we have them: cost, latency, accuracy tradeoffs are real)
You aren't ambitious
Hiring Process
Resume screen
1:1 with founder
Technical deep-dive on past ML work
Work through a real problem with the team
Offer
We strongly encourage applicants from underrepresented backgrounds to apply. Diverse teams build better products - see value #5.
#J-18808-Ljbffr