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For Companies At a Glance
- Tasks: Lead the design and optimisation of AI/ML models for blockchain data analysis.
- Company: Join a leading company in blockchain analytics, shaping the future of crypto.
- Benefits: Enjoy remote work flexibility and competitive salary up to £130,000.
- Why this job: Be at the forefront of AI innovation in the exciting world of blockchain technology.
- Qualifications: Experience in AI/ML projects, proficiency in Python, and knowledge of TensorFlow or PyTorch required.
- Other info: This role is fully remote and does not offer sponsorship.
The predicted salary is between 78000 - 182000 £ per year.
Senior AI/ML Engineer
Fully Remote
£100,000–£120,000 + benefits
About the Role
Our client, a blockchain analytics scale-up, is looking for a Senior AI/ML Engineer to join their expanding team. They’re scaling their AI capabilities and need someone passionate about applying cutting-edge machine learning and LLM techniques to real-world crypto data.
You’ll work directly with a Staff AI/ML Engineer who has built advanced ML teams in the past, driving projects that power their platform – used by investors to discover opportunities, perform due diligence, and defend portfolios.
Key Responsibilities
- Designing, implementing, and maintaining AI/ML models to analyse blockchain data at scale.
- Translating complex datasets into insights that inform investment and trading strategies.
- Working with product teams to build AI-powered features directly into the core platform.
- Staying on top of developments in AI, ML, and blockchain – and experimenting with new techniques.
- Helping to shape best practices and mentor others as the AI function grows.
Your work will focus on delivering high-value, product-driven AI features, including:
- Automated wallet and address labelling through AI and NLP.
- NFT and asset price estimation models.
- Advanced analytics to detect patterns and behaviours across blockchain data.
- Integrating LLM-based capabilities into customer-facing products.
What We’re Looking For
- 3–6 years of experience in Data Science or ML Engineering.
- Strong Python skills and hands-on experience building end-to-end ML solutions.
- Interest in blockchain, crypto, or fintech (commercial crypto experience a plus).
- Experience with GCP or similar cloud environments.
- Familiarity with modern LLMs or AI APIs.
- Someone who experiments in their spare time, reads papers, and keeps up with the latest in AI.
- Collaborative and proactive, with the ability to thrive in a remote, fast-paced environment.
Interview Process
- Culture fit interview.
- Technical discussion with the AI Lead.
- Technical test (general DS/ML best practices).
- Final panel interview.
Senior AI Engineer employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior AI Engineer
✨Tip Number 1
Familiarise yourself with the latest trends in AI and blockchain technologies. Follow industry leaders on social media, read relevant blogs, and participate in online forums to stay updated. This knowledge will not only help you during interviews but also demonstrate your passion for the field.
✨Tip Number 2
Network with professionals in the AI and blockchain sectors. Attend virtual meetups, webinars, or conferences to connect with like-minded individuals. Building relationships can lead to referrals and insider information about job openings, including our position at StudySmarter.
✨Tip Number 3
Showcase your projects and contributions on platforms like GitHub or LinkedIn. Highlight any AI/ML models you've developed, especially those related to blockchain data analysis. This practical demonstration of your skills can set you apart from other candidates.
✨Tip Number 4
Prepare for technical interviews by practising coding challenges and system design questions specific to AI/ML. Use platforms like LeetCode or HackerRank to sharpen your skills. Being well-prepared will boost your confidence and improve your chances of landing the job.
We think you need these skills to ace Senior AI Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with AI/ML projects, particularly those involving blockchain data analysis. Use specific examples to demonstrate your expertise in frameworks like TensorFlow or PyTorch.
Craft a Compelling Cover Letter: In your cover letter, express your passion for blockchain and crypto. Discuss how your skills align with the responsibilities of the role, especially your ability to mentor junior engineers and collaborate across teams.
Showcase Relevant Projects: Include a section in your application that showcases relevant projects you've worked on. Detail your role, the technologies used, and the impact of these projects, particularly in relation to AI/ML and blockchain.
Highlight Communication Skills: Since this is a remote position, emphasise your excellent communication skills. Provide examples of how you've effectively collaborated with teams across different time zones in previous roles.
How to prepare for a job interview at Harnham
✨Showcase Your AI/ML Expertise
Be prepared to discuss your previous projects in detail, especially those involving AI and machine learning. Highlight specific frameworks you've used, like TensorFlow or PyTorch, and explain how you applied them to solve real-world problems.
✨Demonstrate Your Passion for Blockchain
Since the role is focused on blockchain analytics, make sure to express your enthusiasm for the technology. Share any personal projects or research you've done related to blockchain, crypto, or Web3 to show your genuine interest.
✨Prepare for Technical Questions
Expect technical questions that assess your problem-solving skills and understanding of AI/ML concepts. Brush up on key algorithms, data structures, and the latest trends in AI and blockchain technologies to impress your interviewers.
✨Emphasise Collaboration Skills
As this role involves working with cross-functional teams, be ready to discuss your experience collaborating with product and engineering teams. Provide examples of how you've successfully integrated AI/ML solutions into existing platforms and enhanced user experiences.
