Machine Learning Engineer

As a Machine Learning Engineer at our company, your role will involve designing, developing, deploying, and maintaining scalable ML solutions in a cloud-native environment. You will work with data scientists, engineers, and product teams to translate business requirements into ML solutions. Key responsibilities include: - Designing and implementing machine learning models and pipelines using AWS SageMaker and related services. - Developing and maintaining robust data pipelines for training and inference workflows. - Collaborating with teams to implement MLOps best practices such as CI/CD for ML, model versioning, monitoring, and retraining strategies. - Optimizing model performance and ensuring scalability and reliability in production environments. - Monitoring deployed models for drift, performance degradation, and anomalies. - Documenting processes, architectures, and workflows for reproducibility and compliance. Qualifications required for this role include: - Strong programming skills in Python and familiarity with ML libraries such as scikit-learn, TensorFlow, and PyTorch. - Solid understanding of machine learning algorithms, model evaluation, and tuning. - Hands-on experience with AWS ML services, especially SageMaker, S3, Lambda, Step Functions, and CloudWatch. - Experience with data engineering tools like Apache Airflow, Spark, and Glue for workflow orchestration. - Proficiency in MLOps tools and practices like MLflow, Kubeflow, CI/CD pipelines, Docker, and Kubernetes. - Familiarity with monitoring tools and logging frameworks for ML systems. - Excellent problem-solving and communication skills. Preferred qualifications include AWS Certification (e.g., AWS Certified Machine Learning Specialty), experience with real-time inference and streaming data, and knowledge of data governance, security, and compliance in ML systems. This is a full-time position located in either Kochi or Bangalore on a hybrid basis.,