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- Tasks: Build and scale AI/ML models for blockchain analytics and collaborate on innovative projects.
- Company: High-growth SaaS platform known as the Bloomberg for crypto.
- Benefits: Competitive salary, equity, performance bonus, and fully remote work.
- Why this job: Join a senior team and shape the future of AI in blockchain.
- Qualifications: 3-6+ years in data science/ML, strong Python skills, and interest in crypto.
- Other info: Dynamic startup environment with opportunities for mentorship and growth.
The predicted salary is between 78000 - 90000 £ per year.
Do you have 4+ years of hands-on ML experience and enjoy deploying models into production?
Have you worked with GenAI / LLMs and modern ML tooling in real systems?
Are you interested in crypto, blockchain, and applying ML to complex on-chain data?
A Series B, high-growth SaaS platform delivering institutional-grade blockchain intelligence is hiring a Senior AI/ML Engineer. Often described as the Bloomberg for crypto, the platform helps investors discover opportunities, perform due diligence, and defend portfolios using AI-driven insights.
This is a senior, hands-on role for someone strong across data science, applied ML, and cloud deployment, who wants to work in a lean team with real ownership.
Why join?
You’ll join a small, senior AI/ML team working on core product features such as:
- Large-scale wallet labelling and behavioural analysis
- NFT price estimation using ML
- Trading and risk signals built on blockchain data
The environment is fast-moving, product-led, and AI-first, with genuine room to shape how ML is applied across the platform.
Requirements
- 4-7+ years of professional experience in Data Science / ML roles
- Strong data science foundations (EDA, feature engineering, model evaluation, validation)
- Hands-on experience with ML models in production
- Cloud & MLOps exposure (GCP preferred; AWS/Azure acceptable)
- Experience with GenAI / LLMs (commercial or serious hands-on experimentation)
- Strong Python and modern ML tooling (e.g. scikit-learn, XGBoost, TensorFlow or PyTorch)
- Clear interest in crypto / blockchain (commercial experience a plus, curiosity required)
Responsibilities
- Build, train, and improve ML models on large-scale blockchain datasets
- Take models from exploration to production, working closely with engineering
- Apply GenAI / LLM approaches where they add real product value
- Maintain high DS/ML standards across experimentation, monitoring, and iteration
- Contribute to best practices in a lean, senior AI team
Key details
- Salary: up to ~£135k base + equity (4-year vest, 1-year cliff) + bonus
- Location: Fully remote (UK)
- Stack: Python, GCP, ML frameworks, LLM APIs
- Visa: Cannot sponsor
- Team: Senior, small, highly technical
If you’re a senior ML engineer with strong DS fundamentals, real deployment experience, and a genuine interest in crypto, this is a high-impact role with a lot of ownership.
Interested? Please apply below.
Senior MLE - Blockchain AI employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior MLE - Blockchain AI
✨Tip Number 1
Network like a pro! Reach out to folks in the blockchain and AI space on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can get you in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML models and projects related to blockchain analytics. We want to see what you can do, so make it easy for potential employers to check out your work.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical skills and be ready to discuss your past projects in detail. We recommend practising common ML and blockchain-related questions to really impress the interviewers.
✨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 Senior MLE - Blockchain AI
Some tips for your application 🫡
Show Your Passion for Blockchain: Make sure to highlight your interest in blockchain and crypto in your application. We want to see that you’re not just skilled, but also genuinely excited about the field and its potential.
Tailor Your Experience: When detailing your experience, focus on projects where you've built and deployed ML models. We love seeing real-world applications, so don’t hold back on the specifics that showcase your skills!
Be Clear and Concise: Keep your application straightforward and to the point. We appreciate clarity, so make sure your achievements and skills shine through without unnecessary fluff.
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 get the ball rolling on your journey with us.
How to prepare for a job interview at Harnham
✨Know Your Blockchain Basics
Make sure you brush up on your blockchain knowledge before the interview. Understand key concepts like decentralisation, smart contracts, and how AI can enhance blockchain analytics. This will show your genuine interest in the field and help you connect with the interviewers.
✨Showcase Your ML Projects
Prepare to discuss specific ML models you've built and deployed. Be ready to explain the challenges you faced, the solutions you implemented, and the impact of your work. This is your chance to demonstrate your hands-on experience and problem-solving skills.
✨Familiarise Yourself with Their Tech Stack
Since the role involves Python, GCP, and TensorFlow/PyTorch, make sure you're comfortable discussing these technologies. If you have experience with LLM APIs, highlight that too! Being able to speak their language will give you an edge.
✨Emphasise Collaboration and Mentorship
As part of a small team, collaboration is key. Be prepared to talk about how you've worked with cross-functional teams in the past and how you can mentor others in best practices. This shows you're not just a tech whiz but also a team player.
