Lead Machine Learning Engineer
We are helping Fyxer AI hire a Lead Machine Learning Engineer.
Fyxer AI is London's fastest growing AI company. Since launching in April 2024, Fyxer AI has gone from $0 to $30m in ARR and raised a $30m Series B from top investors. They have built a best-in-class AI-powered email & meeting assistant. It works inside your inbox to organise your emails, draft your replies, and take meeting notes, so you can stay focused on your top priorities. It thinks like you. Writes like you. Remembers everything you’ve said and done at work. And it’s changing how professionals work, everywhere.
We're helping them hire a Lead Machine Learning Engineer.
WHAT ARE THEY BUILDING?
Walk around the average office and you’ll see people’s days taken up by emails, Slack and meetings instead of real work.
People in client facing roles - think estate agents, insurance brokers, recruiters - feel this pain most acutely. Instead of meeting clients, they spend hours doing admin. Following up. Scheduling meetings, then taking notes on them. Answering questions they’ve been asked a thousand times. Sorting through the mess that is their inbox.
Fyxer has built an AI executive assistant that looks at all your emails, messages and meetings, and uses that knowledge to answer your email, schedule meetings, take next steps from meetings and organise your inbox.
Big tech has failed to build anything useful for this type of customer, and there isn’t a startup they know that’s doing this that even has $1m ARR. Two of Fyxer’s co-founders spent 8 years running an executive assistant agency, providing a manual service for what they’re now automating using AI.
No one understands this problem space like they do, and they are building a world-class company that is well on their way to solving it.
JOB DESCRIPTION
The Lead Machine Learning Engineer will own the development and productionisation of machine learning systems across Fyxer’s core product. You will lead ML work wherever it creates meaningful leverage – from predictive modelling and recommendation systems to ranking, classification, and decision intelligence embedded directly into the user experience.
You will:
- Design and implement end-to-end ML systems — from problem framing and feature design through modelling, evaluation, deployment, and monitoring
- Develop predictive models, ranking systems, recommendation engines, and classification models that power real user workflow.
- Build rigorous offline evaluation frameworks and design online experiments to measure real product impact
- Work closely with engineering to ensure models are deployed cleanly into production systems with strong attention to latency, reliability, and observability
- Define how features are generated, stored, versioned, and served in production
- Design retraining and monitoring strategies to ensure model performance remains robust over time
- Translate ambiguous product problems into structured modelling approaches
- Raise the bar for statistical rigour and experimentation across the company
You will operate with high ownership — from idea to production — and your work will directly shape how Fyxer makes intelligent decisions for customers.
WHAT DOES THEIR IDEAL HIRE LOOK LIKE?
We're looking for a deeply rigorous machine learning engineer who thinks in systems, not just models. They will have:
Core ML Capability
- Strong grounding in statistics and probabilistic thinking
- Experience building and shipping real ML models into production environments
- Comfortable with feature engineering, model selection, and performance evaluation
- Strong understanding of classification, regression, ranking, and recommendation systems
- Experience designing evaluation frameworks (precision/recall tradeoffs, calibration, thresholding, offline vs online validation)
- Comfortable running and interpreting A/B tests
Production & Systems Thinking
- Understands how models live inside real systems — including data pipelines, latency constraints, deployment architecture, and monitoring
- Has worked on model versioning, retraining strategies, and performance monitoring in production
- Can collaborate effectively with backend engineers to integrate models cleanly into product workflows
- Thinks carefully about reliability, failure modes, and edge cases
Technical Stack
- Strong Python skills
- Experience with libraries including PyTorch and/or sci-kit learn
- Comfortable working with SQL and large datasets
- Experience in cloud environments (e.g. GCP, AWS)
- Familiary with modern LLM techniques (e.g. fine-tuning, LoRA) is a plus - but not the core of the role
They care more about depth of understanding than specific tools.
Mindset & Culture
- Genuinely interested in the problem Fyxer is solving
- Customer-obsessed and motivated by product impact
- High agency and ownership - comfortable operating without heavy structure
- Intense and ambitious, but methodical
- Values rigour over hacky experimentation
- Strong product sense - understands that modelling decisions must align with real user outcomes
This is a role for someone who wants to build durable ML capability, not just ship isolated experiments.
COMPENSATION AND BENEFITS:
- Up to £200k base salary + equity
- Private medical insurance
- Private dental insurance
- Pension
- 25 days annual leave
- The opportunity to build the UKʼs fastest growing AI company with a world-class team
INTERVIEW PROCESS:
- Initial call with Fyxer AI team
- Take home technical task + follow-up interview
- Final interview (on-site)
***Fyxer AI values in-person collaboration. Please only apply to this role if you're excited and able to work in central London 4 days per week***