Machine Learning Engineer PhD

This is a remote position. Keystone AI delivers high-impact AI solutions to Fortune 500 clients and fast-growing start-ups. We need a PhD-level Machine Learning Engineer who can move fast from research to production across multiple tech stacks. Key responsibilities: • Research and design advanced machine learning models that solve real customer problems • Prototype, test and optimise models in Python using TensorFlow, PyTorch and scikit-learn • Deploy and monitor solutions on AWS, Azure or GCP with CI / CD and IaC tools • Work with data engineers to build robust data pipelines and feature stores • Translate complex findings into clear business recommendations for stakeholders • Coach client teams and Keystone AI consultants on best ML practices • Contribute to technical pre-sales and proposal work when required Requirements PhD in Machine Learning, Computer Science, Mathematics or similar At least three years of post-doctoral experience delivering ML projects in industry Fluency in Python plus solid knowledge of Java, Scala or C++ Hands-on expertise with deep learning, classical ML and generative models Strong grasp of MLOps, containerisation, microservices and cloud-native architectures Excellent communication in English, written and spoken Desirable Publications or patents in applied AI Experience with time-series forecasting, reinforcement learning or NLP at scale Familiarity with data privacy frameworks in the EU and USA Benefits Direct impact on flagship client projects in finance, retail and healthtech High-end hardware and training budget for continuous learning Flexible location and working hours Competitive daily rate or permanent package scaled to expertise Originally posted on Himalayas