We are looking for a talented Machine Learning Engineer who is passionate about delivering impactful solutions and moving models from research environments into high-performance production systems. Key Responsibilities: Collaborate closely with data scientists and cross-functional teams to integrate machine learning models seamlessly into production systems Implement end-to-end solutions, including architecture design, business logic, deployment and monitoring Perform exploratory data analysis, build baseline models and fine-tune existing architectures to support the data science team Package, containerize, and deploy ML models (Financial, Text, Image) as scalable microservices (using FastAPI, Docker) Stay updated with advancements in machine learning and related technologies to continuously improve our solutions Drive the adoption of rigorous engineering standards and testing practices for ML codebases, ensuring high-quality, reliable ML model releases Key Requirements: Master's or Bachelor's degree in Computer Science, Engineering, or a related field with 2+ years of relevant industry experience Strong understanding of computer science fundamentals, object-oriented programming and software design patterns Strong knowledge of machine learning fundamentals and proficiency in data analysis Proficiency in Python, SQL, FastAPI or other RESTful API architectures and AWS Familiarity with numpy, pandas, torch, scikit-learn and other Python libraries commonly used in machine learning We believe: Diversity is a competitive advantage.
