About the Role We are looking for a Senior Machine Learning Engineer to design, build, and deploy scalable machine learning solutions that power intelligent products and data-driven decision-making. You will work closely with data scientists, software engineers, product managers, and stakeholders to develop production-ready ML systems, optimize model performance, and drive innovation across the organization.
Responsibilities Design, develop, deploy, and maintain machine learning models for production environments. Build scalable ML pipelines for data processing, model training, evaluation, and monitoring. Collaborate with cross-functional teams to translate business requirements into ML solutions. Optimize model performance, accuracy, latency, and scalability. Develop and maintain feature-engineering and data-preprocessing pipelines. Implement MLOps best practices, including CI/CD, model versioning, monitoring, and automated retraining. Work with cloud platforms and distributed computing frameworks to support large-scale ML workloads. Mentor junior engineers and contribute to engineering standards and best practices. Stay current with advancements in AI, machine learning, and generative AI technologies.
Requirements Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or a related field.5+ years of experience developing and deploying machine learning solutions in production. Strong proficiency in Python and ML frameworks such as Tensor Flow, PyTorch, or Scikit-learn. Experience building data pipelines using SQL and tools such as Spark, Airflow, or Kafka. Hands-on experience with cloud platforms (AWS, Azure, or Google Cloud Platform). Strong understanding of MLOps practices, Docker, Kubernetes, CI/CD, and model monitoring. Experience with REST APIs and integrating ML models into production applications. Knowledge of software engineering best practices, testing, and version control (Git). Excellent problem-solving, communication, and collaboration skills.