As our portfolio of AI-driven solutions continues to expand, we’re looking for an experienced Machine Learning Engineer to join our high-impact data science team. This role offers the opportunity to work across trading, operations, and support functions - delivering production-grade machine learning systems that solve real business problems. You’ll collaborate with data scientists, software engineers, and commercial stakeholders to design, build, and deploy models that drive decision-making and innovation. From project scoping to model deployment, you’ll have visibility and influence across the full ML lifecycle. 🔧 Core Responsibilities
- Act as a thought partner to commercial teams, identifying high-value opportunities for AI/ML applications
- Lead the design, development, and deployment of machine learning systems, with a focus on NLP, LLMs, and Generative AI
- Prioritize projects based on business impact and evolving market conditions
- Collaborate with cross-functional teams to gather requirements and align solutions with strategic goals
- Integrate ML solutions - including GenAI - into existing platforms to ensure seamless user experiences and scalable adoption
- Participate in code reviews, experiment design, and tooling decisions to maintain high engineering standards
- Share knowledge and mentor colleagues to build machine learning fluency across the organization
Master’s degree in Computer Science, Data Science, Machine Learning, or related field (Ph.D. preferred) 5–7+ years of experience developing and deploying ML models in production environments Deep expertise in Python, with clean, modular, well-documented coding practices Proven experience applying LLMs to solve business problems, with strong understanding of GenAI design patterns Proficiency with ML frameworks and libraries: TensorFlow, PyTorch, Transformers Familiarity with AWS and containerization tools like Docker Strong grasp of ML fundamentals: deep learning, generative models, NLP techniques (sentiment analysis, entity recognition, disambiguation) Excellent communication skills - able to translate complex technical concepts for non-technical audiences