Job Summary We are seeking a highly skilled and motivated Machine Learning Engineer to join our dynamic team at Speria MTech. The ideal candidate will play a crucial role in designing, building, and deploying scalable machine learning and optimization systems that drive real-time decision-making. The role spans data processing, feature engineering, model development, optimization modeling, and production deployment, contributing to systems that transform operational data into predictions and automated actions. We seek a solution-oriented individual who can provide answers rather than just identify problems. Embracing continuous change is key, as innovation and improvement are integral to Speria MTech's culture. This person should have a service-minded attitude, demonstrating a passion for enhancing the work of others and simplifying processes for stakeholders. Essential Functions & Responsibilities Essential responsibilities include and functions of the Machine Learning Engineer are: • Design and build machine learning and optimization pipelines • Develop and deploy production-grade models • Build feature pipelines using distributed systems (e.g., Spark) • Collaborate with data engineering on data readiness • Develop decisioning systems for automated actions • Monitor model performance and improve continuously Qualifications, Skills, and Experience • Bachelor's or Master's degree in relevant field (MS may qualify with 1-2 years; BS typically 4-6 years) • 2-4 years experience in Machine Learning or optimization • Experience deploying Machine Learning systems in production • Familiarity with Machine Learning flow, Databricks, CI/CD • Strong Python programming (production-level) • Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) Preferred Skills • SQL and Apache Spark experience • Feature engineering pipelines for Machine Learning • Git, CI/CD, reproducible workflows • Experience with real-time systems • Familiarity with LLMs, generative AI, and agent-based systems • MS may qualify with 1-2 years; BS typically 4-6 years