Senior Machine Learning Engineer

Company Description We connect skilled professionals with leading companies across India and international markets, focusing on making job searches faster, smarter, and more transparent. Our platform features verified roles across domains such as Information Technology, Product Management, Sales & Marketing, Finance & Accounting, HR & Recruitment, Operations, and Customer Success. We support both experienced professionals and recent graduates by providing up-to-date career opportunities tailored to diverse skill sets. Employers seeking to hire can also partner with us to access a wide pool of qualified candidates and streamlined recruitment support.

Role Description The Senior Machine Learning Engineer will design, build, and deploy scalable machine learning models that power data-driven products and services for our clients. Day-to-day responsibilities include developing end-to-end ML pipelines, performing model training and evaluation, optimizing algorithms for performance, and collaborating with cross-functional teams to integrate ML solutions into production systems. The role involves conducting rigorous data exploration, applying advanced statistical techniques, and ensuring model reliability, fairness, and maintainability. The Senior Machine Learning Engineer will also mentor junior engineers, contribute to technical best practices, and stay current with emerging ML research and tools. This is a full-time remote role, offering flexibility while requiring strong ownership and communication in a distributed team environment.

Qualifications

• Strong foundation in Computer Science and Algorithms, with experience in designing efficient, production-ready solutions.
• Expertise in Neural Networks and Pattern Recognition for solving complex classification, prediction, and recommendation problems.
• Solid understanding of Statistics for experimental design, hypothesis testing, and model evaluation.
• Proficiency in one or more programming languages commonly used for ML (e.g., Python, Java, or C++), and familiarity with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Experience building and deploying ML models at scale using cloud platforms (e.g., AWS, GCP, Azure) and containerization/orchestration tools (e.g., Docker, Kubernetes).
• Ability to work independently in a remote setting, collaborate with product, data, and engineering teams, and communicate complex technical concepts clearly.
• Bachelor's or Master's degree in Computer Science, Data Science, Mathematics, Engineering, or a related field; equivalent practical experience is also considered.
• Background in MLOps, model monitoring, and performance optimization, with attention to data privacy, security, and ethical AI principles.