Machine Learning Engineer

About: Founded with a mission to reduce societal inequalities, the company focuses on harnessing data and insights to drive impactful partnerships. They collaborate with a range of local authorities on various social domains, such as homelessness Their primary offering is a DaaS (Data as a Service) platform tailored to improve frontline support and outcomes for vulnerable residents. They emphasise aligning their work with meaningful results for end-users. They are seeking team members who are passionate about the mission and committed to helping local communities through innovative data solutions. In this role, you‘ll be tasked with designing and building robust, scalable ML pipelines to address real-world challenges, particularly in areas like social care and financial support. Location Remote-first, with the potential for occasional in-person meetings. Benefits Competitive, annually reviewed salary The opportunity to join a mission-driven team focused on resolving key societal issues Flexible working hours to accommodate life commitments, emphasising output over time logged Remote work setup, except for monthly team meetings and occasional client visits Paid training and development opportunities through the appraisal process 25 days of annual leave, excluding bank holidays Company pension plan enrolment Provision of necessary IT equipment (laptop included) Covered travel and accommodation expenses for required in-person meetings Responsibilities Deploy, optimise, and monitor ML models in production, including NLP, decision trees, and logistic regression models Enhance data pipelines using Azure Batch & Azure ML, improving data lineage, quality, and minimising production errors Design and implement high-performance data stores for efficient data processing and retrieval Ensure infrastructure supporting ML models is secure, scalable, and reliable Develop a machine-learning-driven alert system to provide actionable, real-time notifications based on data-driven triggers Collaborate closely within a small, autonomous team, fostering innovation and effectively partnering with data engineering to create cross-functional ML pipelines Requirements & Experience 3-5 years in MLOps or similar roles, with a solid understanding of the ML lifecycle Proficiency in Python or similar languages, and experience with ML frameworks (e.g., PyTorch, XGBoost, LightGBM) Experience with cloud platforms, such as Azure ML Studio & Azure Batch, or comparable environments Skilled in containerisation (Docker, Kubernetes) and CI/CD automation Knowledgeable in predictive modelling, NLP, and various ML techniques Strong problem-solving skills for tackling complex ML system issues Excellent communicator for both technical and non-technical audiences Team-oriented, with a collaborative approach to work