At a Glance
- Tasks: Lead the development of AI systems that predict user actions and enhance client engagement.
- Company: Join Fyxer AI, a fast-growing tech startup revolutionising AI for client-facing professionals.
- Benefits: Hybrid work model, competitive salary, and opportunities for rapid career advancement.
- Other info: Be part of a lean team with significant growth potential and ownership over your projects.
- Why this job: Shape the future of AI while working with a passionate team in a dynamic environment.
- Qualifications: Experience in ML/AI engineering and a strong product-focused mindset.
The predicted salary is between 80000 - 100000 £ per year.
About the Role
As a Lead Machine Learning Engineer at Fyxer AI, you will be a key driver in shaping the future of our AI products. You will own the strategy and execution of building and improving the system for predicting the next action our users (salespeople) should take to move their relationships forward. This role requires a strong sense of autonomy, agency, and ownership, as you will be responsible for a specific business area within a small, highly focused team. We operate in a hybrid model, working Monday-Thursday in our Chancery Lane, London office, and Friday remotely.
What We're Building
Fyxer AI is developing an AI executive assistant designed to tackle the administrative burden faced by client-facing professionals such as estate agents, insurance brokers, and recruiters. Our AI assistant handles emails, schedules meetings, takes notes, manages follow-ups, and organizes inboxes, allowing users to focus on client engagement. Our current focus is predicting the next email a salesperson will send, and in 2026, we aim to predict the next best action a salesperson should take to advance their important relationships.
Our Progress and Values
Since our launch in April 2024, we've achieved significant growth, reaching $30m in ARR and raising a $30m Series B from top investors. We are a lean team of 18 engineers, emphasizing a culture of autonomy, agency, and ownership. Each engineer is empowered to own their business area, including strategy and execution, supported by our data engineering department. We value intense dedication and a proactive approach, offering fast-tracked opportunities for senior roles and responsibilities.
Responsibilities
- Own the development and improvement of the system for predicting the next action users should take.
- Select the best model architecture and overall approach, which will involve a complex system of LLM steps and traditional ML models.
- Pick evaluation metrics and design systems to analyze models in production to identify areas for improvement.
- Identify opportunities to leverage our 60+ person human data team for training or validation datasets.
- Stay current with relevant research to find optimal approaches for our use cases.
- Partner with the CTO to define the collaboration between ML, product engineering, model operations, and human data teams, and to strategize team development.
Requirements
- Proven experience as an ML/AI engineer at a scaleup tech company or as a founder of an AI-focused startup.
- A strong desire to drive strategy in your area, proactively discovering improvements through usage data, research papers, and model evaluation in production.
- Product-focused mindset: ability to translate product goals into technical decisions regarding model architecture, category sets/ontology, evaluation methods, etc.
- Bonus: Extensive experience (large portion of the last 4 years) working with systems involving generative AI.
- Bonus: Prior experience building recommendation systems.
- Demonstrated urgency and intensity in your work.
Our Tech Stack
While not a strict requirement to have worked with every tool, familiarity with our stack is a plus:
- A 60-person custom data annotation platform team for human judgment data.
- API integrations with OpenAI API and Google Vertex AI.
- Typescript for backend code.
- Firestore as our database.
- Firebase Auth for our authentication system.
- Backend deployed on Firebase Functions, utilizing PubSub and Cloud Storage.
- React frontend, with ShadCN for components, TailwindCSS for styling, and React Query for state management.
- Sentry and Google Cloud Logging for monitoring.
- Github Actions for CI/CD.
Lead Machine Learning Engineer employer: Fyxer AI
Fyxer AI is an exceptional employer, offering a dynamic work environment in the heart of London where innovation thrives. With a strong emphasis on autonomy and ownership, employees are empowered to take charge of their projects while benefiting from fast-tracked growth opportunities within a lean, dedicated team. Our hybrid work model promotes a healthy work-life balance, making Fyxer AI an attractive choice for those seeking meaningful and rewarding careers in the rapidly evolving field of AI.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Machine Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to people in your industry on LinkedIn or at events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects and contributions. This gives potential employers a taste of what you can do beyond your CV.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios related to machine learning. We recommend doing mock interviews with friends or using online platforms to boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Lead Machine Learning Engineer
Some tips for your application 🫡
Show Your Passion for AI:When you're writing your application, let your enthusiasm for AI and machine learning shine through. We want to see that you’re not just looking for a job, but that you genuinely care about shaping the future of AI products like ours.
Tailor Your Experience:Make sure to highlight your relevant experience in ML/AI, especially if you've worked in scaleup tech companies or have been involved in AI startups. We love seeing how your background aligns with our mission and the specific role.
Be Clear and Concise:Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon unless it’s necessary. Make it easy for us to see why you’re a great fit for the Lead Machine Learning Engineer position.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, we love seeing applications come directly from our site!
How to prepare for a job interview at Fyxer AI
✨Know Your Stuff
Make sure you brush up on your machine learning fundamentals and the specific technologies mentioned in the job description. Familiarise yourself with generative AI, recommendation systems, and the tech stack Fyxer AI uses. Being able to discuss these topics confidently will show that you're serious about the role.
✨Show Your Strategic Side
Prepare to talk about how you've driven strategy in your previous roles. Think of examples where you've used data to make decisions or improve processes. Fyxer AI is looking for someone who can take ownership, so demonstrate your ability to think proactively and strategically.
✨Be Ready to Collaborate
Since this role involves partnering with the CTO and various teams, be prepared to discuss your experience working in cross-functional teams. Highlight any past collaborations that led to successful outcomes, and show that you value teamwork and communication.
✨Ask Insightful Questions
At the end of the interview, have a few thoughtful questions ready. Ask about the challenges the team is currently facing or how they measure success for the ML models. This shows your genuine interest in the role and helps you understand if it's the right fit for you.
