Machine Learning Research Scientist

Tothemoon
1 year ago
Applications closed

Related Jobs

View all jobs

NLP/LLM Research Scientist (PhD) – Cambridge Hybrid

NLP/LLM Research Scientist (PhD) – Hybrid, Cambridge

Junior Machine Learning Engineer

Principal Data Science and Machine Learning Researcher

Bioprocess Upstream Data Scientist

Hybrid Research Data Scientist: AI & ML for Finance

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.

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.

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

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.