Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Machine Learning Research Scientist

Tothemoon
1 year ago
Applications closed

Related Jobs

View all jobs

Machine Learning Research Scientist

Machine Learning Research Engineer (Foundational Research)

Senior Research Scientist: Data Science and Machine Learning AIP

Machine Learning Research Engineer

Research Scientist | Diffusion Modelling | Python | PyTorch | Machine Learning | Generative Modelling | Hybrid, London

Research Intern in Machine Learning, Machine Intelligence

About Tothemoon Tothemoon is a user-centric, multiservice digital assets trading platform. At Tothemoon, we prioritize what matters most in finance: reliability. Whether it’s buying, selling, exchanging, or investing in cryptocurrencies, you can trust us to protect your financial interests and propel you towards a prosperous future. Join a rapidly growing community of users who choose Tothemoon for their digital transactions. One of our products is a  fast-growing, crypto-native investment fund focused entirely on DeFi. We see DeFi as a dynamic space with fewer competitive players, where traditional finance is slow to adapt due to regulatory constraints. This creates a unique opportunity to disrupt the market with innovative, AI-driven trading systems. We’re on a mission to build the future of trading in DeFi by creating AI-driven systems that trade autonomously and scale with the market, reducing human involvement. Machine learning will be at the heart of our trading strategies, pushing the boundaries of quantitative research and providing smarter, more scalable solutions. Note: No experience in trading or DeFi is required. We’re a tech company at our core and are looking for candidates with experience in fast-moving, data-driven environments. What You’ll Do: We’re looking for an ML Research Scientist with expertise in time series modeling and forecasting. If you’ve developed models for forecasting traffic or predictive analytics in industries like e-commerce or social media, this is a great fit. You’ll focus on building new machine learning models from scratch, using time series analysis to predict and model dynamic, decentralized markets. Your work will help replace traditional human-driven quantitative models with autonomous AI agents that learn and adapt in real-time. If you're excited about developing cutting-edge models and shaping the future of DeFi trading, this is a unique opportunity. Why Join Us? Competitive salary  that reflects your value. Blended work  – work from home or at our amazing office with the breathtaking sea view.  Paid holidays  to relax and recharge. Opportunities for  continuous learning  and  career growth . A dynamic, inclusive team that values creativity, humor, and  out-of-the-box  thinking. We offer competitive compensation, with the possibility of profit-sharing based on your contributions to building and refining our trading strategies. As one of the first ML Engineers or ML Research Scientists to join the team, you’ll have the opportunity to shape our vision and share in the success as we grow. At Tothemoon, we embrace diversity, equity, and inclusion. No matter who you are or where you’re from, we encourage you to bring your talents to the table. We assess candidates purely on their professional skills and experience. Are you ready to help us shape the future of crypto? Apply today! Powered by JazzHR

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.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.