Senior ml engineer - fintech

We are seeking a skilled Machine Learning Engineer to join our team, leading the development and deployment of cutting-edge AI/ML models. In this role, you will build and maintain scalable solutions in cloud-native environments, collaborate with cross-functional teams, and mentor junior engineers to drive innovation. You will also play a key part in designing automated pipelines, ensuring data quality, and advocating best practices in MLOps to solve impactful business challenges and contribute to meaningful projects in a dynamic and supportive environment. When applying please remember to include your CV. Join our team as a Machine Learning Engineer and make a meaningful impact while working in a supportive and collaborative environment. You will be part of our Fin Tech Client’s Data Centre for Excellence, working with data scientists, engineers, and analysts. This role is ideal for someone who creates value through innovation and teamwork. You will be working closely with our cross-functional teams and business leaders to drive strategic decision-making across multiple regions, including the UK, Europe, Australia, and New Zealand. We believe in empowering you to grow your skills, and you will have the opportunity to leverage your machine-learning expertise to solve key business challenges. We promote a healthy work-life balance and offer a culture where your contributions are recognised. Responsibilities Lead cross-functional teams including data scientists, data engineers, and data analysts, as well as manage expectations of business stakeholders and work to understand business requirements and develop solutions that have an impact on the bottom line. Own the end-to-end development of AI & ML models for real-time and batch-based products, as well as running customer-facing services (APIs) in AWS cloud-based environments. Drive and advocate the adoption of best practices in cloud-native MLOps (monitoring + alerting). Create and be responsible for data pipelines and automation processes that enhance efficiency, accuracy, and quality in data collection and data preparation. Mentor junior ML engineers to support their growth and encourage upskilling. Document analytical processes, methodologies, and findings to ensure clarity, reproducibility, and knowledge sharing across teams. Requirements Master’s degree in STEM (Computer Science, ML/AI, Physics, Engineering), along with 5+ years of experience delivering measurable value through data in a commercial setting. Expert in Python 3.12+ and latest versions of frameworks, including Scikit-learn, Numpy, and Pandas with practical Data Science experience of Spark SQL and Jupyter notebooks. Experience with MLOps pipelines on AWS and building, training, testing, and deploying ML models at scale on cloud-native infrastructure. Experience with CI/CD tooling and AWS products like EC2, S3, Cloud Watch, and AWS CDK. Experience with monitoring and alerting solutions such as New Relic, Datadog, or Pager Duty. Strong software testing approach to ensure high test coverage for financial use cases. Strong understanding of the structure and suitability of different ML models and approaches for training trade-offs with experience in testing and accuracy for business performance. Well-versed in version control, with practical experience of Git+Gitflow on Github or Gitlab. Excellent communication skills, able to translate technical findings into business insights. Comfortable managing priorities in a fast-paced and dynamic work environment. A self-starter, detail-oriented who thrives on integrity, initiative, team-playing, and results. Desire to stay up-to-date and experiment with the latest Gen AI research. Preferred Qualifications (Nice-to-Have) Ph D in STEM, plus 2+ years delivering value through data in a commercial environment. Experience in engineering leadership across multiple teams & product roadmaps. Experience containerising ML models for AWS EKS Kubernetes and serverless serving. Experience with Lang Chain framework and prompt engineering on LLMs via LLMOps. Experience with Terraform and building resilient cloud infrastructure as code (Ia C). Ideally working knowledge of Py Torch and training deep ML models from scratch. Exposure to financial services and challenges with pricing and credit decision-making. Competitive Offer Competitive salary and benefits package. Opportunities for professional growth and career development in an Automation role. Dynamic and collaborative work environment. Flexible work schedule and fully remote work. 25 days of annual paid leave. Additional health insurance via UNIQA. Multi Sport card. #J-18808-Ljbffr