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

Machine Learning Software Engineer, Research

AIML - Machine Learning Research (Speech Translation)

Machine Learning Engineer/Researcher

Machine Learning Engineer/Researcher

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.

Careers Jobs

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.

Jobs

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.

Education Jobs

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.