ML Researcher - Amsterdam/Remote

Machine Learning ResearcherLocation: Amsterdam / RemoteOur client is a rapidly growing proprietary trading firm specialising in systematic trading and market-making across global futures markets. Combining a research-first culture with significant investment in technology and infrastructure, the firm empowers researchers to take ownership of ideas and directly influence trading performance. As the business continues to expand, they are seeking an exceptional Machine Learning Researcher to develop next-generation quantitative trading strategies and contribute to the firm's long-term research agenda.The OpportunityThis is an opportunity to join a highly collaborative team at the intersection of machine learning, quantitative research, and systematic trading. You will work alongside experienced Quant Researchers, Traders, and Technology teams to identify alpha opportunities, build predictive models, and deploy research into live production environments.The ideal candidate will have a strong academic background in machine learning or a related quantitative field, alongside a demonstrated track record of high-quality research through leading publications, competitive internships, or industry experience.ResponsibilitiesConduct cutting-edge machine learning research for systematic trading and market-making strategiesDevelop predictive models using large-scale financial, market microstructure, and alternative datasetsGenerate, evaluate, and refine alpha signals across global futures and other liquid marketsCollaborate closely with Quant Researchers, Traders, and Portfolio Managers to translate research into production strategiesBuild and enhance research infrastructure, modelling frameworks, and data pipelinesAnalyse large and complex datasets to extract meaningful insights and uncover inefficienciesPresent research findings and recommendations to both technical and non-technical stakeholdersStay at the forefront of developments in machine learning, artificial intelligence, and quantitative financeRequirementsPhD or Master's degree in Machine Learning, Computer Science, Mathematics, Statistics, Physics, Engineering, or another highly quantitative disciplineStrong foundation in machine learning, statistical modelling, optimisation, and predictive analyticsExcellent Python programming skills with experience working in research environmentsExperience handling and analysing large-scale datasetsAbility to thrive in a fast-paced, highly collaborative environmentPreferred BackgroundCandidates are particularly encouraged to apply if they possess one or more of the following:Publications at leading machine learning or AI conferences, including NeurIPS, ICML, ICLR and AISTATSInternship or full-time experience at a leading proprietary trading firm, hedge fund, quantitative trading company, or top-tier technology firmAcademic background from a leading European or global university with a strong reputation in quantitative research and machine learningExperience applying machine learning techniques to real-world prediction, optimisation, or decision-making problemsExposure to financial markets, quantitative research, algorithmic trading, or market-making environments