Senior AI/ML Engineer - Crypto/Blockchain

Harnham
Bristol
10 months ago
Applications closed

Related Jobs

View all jobs

Senior AI/ML Data Engineer — Build & Deploy Models

Senior AI Data Engineer - ML, NLP & MLOps

Senior Lead Analyst - Data Science_ AI/ML & Gen AI - UK

Senior Data Scientist - AI/ML (CADD) December 12, 2025

Senior Azure Data Engineer

Senior Data Scientist (Applied AI)

Salary:£90,000 - £110,000


Location:Remote (team based internationally, but AI division in UK)


Join a leading cryptocurrency analytics firm that empowers investors by identifying market opportunities! They're looking to expand their AI & ML capabilities - driving innovation in blockchain analytics.


ROLE AND RESPONSIBILITIES

  • Design, develop, and deploy AI/ML models to analyze blockchain data, uncovering critical insights for cryptocurrency investors.
  • Optimize model performance and scalability to handle vast blockchain datasets.
  • Collaborate with product managers and engineers to integrate AI/ML models into the platform, enhancing analytical capabilities.
  • Stay ahead of advancements in AI, ML, and blockchain technologies to drive innovation.
  • Mentor junior engineers and promote best practices in AI/ML development.


SKILLS AND EXPERIENCE

Required

  • Strong experience in AI Engineering, ML Engineering, or Data Science.
  • Hands-on experience designing and implementing ML models in production.
  • Expertise in blockchain, cryptocurrency, or financial analytics.
  • Proficiency in Python, TensorFlow, PyTorch, or similar frameworks.
  • Excellent communication skills and the ability to work in a fast-paced environment.


This role is fully remote andcannot sponsor.


Apply below!

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.

Data Science Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Thinking about switching into data science in your 30s, 40s or 50s? You’re far from alone. Across the UK, businesses are investing in data science talent to turn data into insight, support better decisions and unlock competitive advantage. But with all the hype about machine learning, Python, AI and data unicorns, it can be hard to separate real opportunities from noise. This article gives you a practical, UK-focused reality check on data science careers for mid-life career switchers — what roles really exist, what skills employers really hire for, how long retraining typically takes, what UK recruiters actually look for and how to craft a compelling career pivot story. Whether you come from finance, marketing, operations, research, project management or another field entirely, there are meaningful pathways into data science — and age itself is not the barrier many people fear.