Machine Learning Engineer

Join an innovative team where data science, machine learning, and software engineering come together to solve complex business challenges. This role is ideal for someone who enjoys bridging the gap between experimentation and production, transforming analytical models into scalable, reliable solutions that drive tangible business outcomes. You will collaborate with data scientists, engineers, and business stakeholders to develop intelligent systems, improve operational efficiency, and implement cutting-edge AI solutions. This is a hands-on engineering role offering exposure to modern machine learning, MLOps, cloud technologies, and large-scale data environments. If you are passionate about turning ideas into production-ready solutions and want to work at the forefront of AI and automation, this opportunity is for you. Key Responsibilities: • Design, build, deploy, and maintain machine learning and AI solutions in production environments • Develop intelligent systems for document processing, information extraction, automation, forecasting, classification, and optimisation • Transform data science models and prototypes into scalable, production-ready applications and services • Build and maintain APIs, pipelines, and automated scoring solutions • Implement CI/CD, testing, orchestration, monitoring, and model management practices • Monitor model performance, data quality, drift, and operational reliability • Collaborate with software engineers and technical teams to integrate machine learning solutions into business systems • Define success metrics and evaluate the business impact of deployed solutions • Contribute to code reviews, technical documentation, and knowledge sharing initiatives Job Experience and Skills Required: • Education: • Degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field • Experience: • Proven experience developing production-grade machine learning and AI solutions • Strong software engineering experience using Python • Experience deploying models through APIs, pipelines, or automated workflows • Experience working with large and complex datasets • Technical Skills: • Python and data science libraries • SQL and advanced data analysis • REST API development • Git version control • Automated testing and software development best practices • Machine learning model development, evaluation, and optimisation • CI/CD and software deployment practices • Advantageous: • MLOps tooling and model lifecycle management • Snowflake, Snowpark, dbt, or similar data platforms • Containerisation and cloud-based deployments • XGBoost, LightGBM, or similar modelling frameworks • OCR, document intelligence, and information extraction solutions • Financial services, lending, credit risk, fraud, or regulated industry experience • Additional Requirements: • Strong analytical and problem-solving abilities • Excellent communication and stakeholder engagement skills • Ability to balance technical excellence with business value • Strong ownership mindset and commitment to delivering measurable outcomes #J-18808-Ljbffr