Machine Learning Engineer

Job Description: Machine Learning EngineerPosition: Machine Learning Engineer Location: Bhubaneswar Department: Technology / Data Science Reports To: Manager About the RoleWe are looking for a skilled and motivated Machine Learning Engineer to join our team. The role involves designing, developing, and deploying machine learning models and scalable AI solutions that drive business value. You will work closely with data scientists, software engineers, and product teams to transform data into actionable insights and intelligent applications. Key Responsibilities Design, build, train, and deploy machine learning models for real-world applications. Collaborate with data scientists to turn prototypes into production-ready solutions. Preprocess, clean, and analyze large datasets to prepare them for modeling. Optimize model performance, scalability, and accuracy. Deploy ML models using frameworks such as TensorFlow, PyTorch, Scikit-learn, or similar. Develop APIs or integrate ML models into existing products and platforms. Monitor model performance and retrain as necessary to ensure accuracy and reliability. Research and implement new algorithms, techniques, and best practices in AI/ML. Work with cloud platforms (AWS, Azure, GCP) for large-scale ML pipelines and deployment. Document processes, maintain code repositories, and follow MLOps best practices. Required Qualifications Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or related field. Strong knowledge of Python and ML libraries (Scikit-learn, TensorFlow, PyTorch, Keras). Proficiency in data preprocessing, feature engineering, and model evaluation techniques. Experience with SQL/NoSQL databases and handling large datasets. Understanding of machine learning algorithms (supervised, unsupervised, NLP, deep learning). Familiarity with cloud platforms (AWS Sagemaker, GCP AI, Azure ML) and containerization (Docker, Kubernetes). Strong problem-solving skills with attention to detail. Preferred Qualifications (Good to Have) Experience with MLOps tools (MLflow, Kubeflow, Airflow). Exposure to Natural Language Processing (NLP) or Computer Vision projects. Knowledge of big data frameworks (Hadoop, Spark). Prior experience in deploying models into production at scale. Contributions to open-source ML projects or research publications. Soft Skills Strong analytical and critical thinking. Excellent communication and teamwork. Ability to work in an agile and fast-paced environment. Curiosity and willingness to learn emerging AI technologies. Compensation & Benefits Competitive salary with performance-based incentives. Health insurance and other employee benefits. Opportunities for professional growth and certifications.