Senior Machine Learning Engineer

Job Title: Senior Machine Learning Engineer Experience Required: 7–10 years Employment Type: Full-Time Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or a related quantitative field Role Overview: We are looking for a highly skilled and innovative Senior Machine Learning Engineer to join our team. This role involves designing, developing, and maintaining scalable machine learning models and solutions, while collaborating with cross-functional teams to ensure alignment with business and technical objectives. Key Responsibilities: Design, develop, test, and deploy scalable machine learning models and pipelines for high-impact business use cases. Collaborate with data scientists, product managers, software engineers, and ML engineers to ensure successful implementation and integration of ML solutions. Perform research, experimentation, customization, and evaluation of ML algorithms; conduct training, tuning, testing, and deployment. Work with large-scale structured and unstructured data to build and continuously improve advanced ML models. Maintain, update, and monitor existing ML systems for performance and relevance. Lead development efforts for complex products and platforms, including architecture, analysis, coding, testing, and deployment of robust cloud-native solutions. Develop and maintain ML pipelines that support both batch and real-time inference. Drive innovation through research and evaluation of emerging tools, technologies, and frameworks in machine learning and data engineering. Mentor and guide junior engineers and team members. Represent the engineering team in internal and external technical forums. Provide critical feedback on product design and testing strategies to ensure best-in-class delivery. Ensure code quality and compliance with cloud and software engineering standards. Required Qualifications: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. 7–10 years of hands-on experience in ML engineering, with a proven track record of production-level deployments. Expertise in Python; working knowledge of Golang is a plus. Experience building and deploying ML models in real-world applications and integrating them with enterprise systems. Strong understanding of microservices architecture, containerization, and orchestration platforms like Kubernetes. Solid experience with cloud-based development and deployment practices (e.g., AWS, Azure, GCP). Knowledge of distributed systems and cloud subsystems design. Skills & Competencies: Deep understanding of machine learning principles, statistical modeling, and data processing workflows. Experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn) and data pipeline tools (e.g., Airflow, Kafka). Experience with containerization (Docker) and orchestration (Kubernetes). Strong problem-solving and analytical skills. Ability to write clean, efficient, and testable code. Excellent verbal and written communication skills. Strong leadership, mentoring, and collaboration abilities. If you're passionate about solving complex problems at scale using machine learning, and thrive in a dynamic, fast-paced environment—this is the opportunity for you.