Machine Learning Engineer – AI/ML Platform & MLOps

About the Role

We are looking for an experienced Machine Learning Engineer specializing in AI/ML platforms and MLOps to join our team. This full-time position based in Kolkata involves building, deploying, scaling, and monitoring comprehensive machine learning solutions across the entire AI lifecycle including data and feature engineering, model development, deployment, and governance. The successful candidate will architect robust AI platforms and promote enterprise-level adoption of AI technologies through engineering best practices.

Key Responsibilities

• Develop scalable data pipelines capable of handling both structured and unstructured data to support AI initiatives.
• Create reusable frameworks for feature engineering, feature stores, and ensure data quality validation.
• Design, train, optimize, and deploy machine learning models addressing various business challenges such as demand forecasting, churn prediction, recommendation engines, optimization, NLP, classification, regression, and time-series analysis.
• Develop AI-driven business applications and production-grade machine learning services including APIs, microservices, inference, and scoring engines for real-time or batch processing.
• Implement comprehensive MLOps pipelines encompassing CI/CD processes, automated deployments, experiment tracking, and model version control.
• Establish automated model retraining and continuous delivery pipelines suitable for cloud and on-premise platforms.
• Deploy monitoring systems to detect model drift, data drift, concept drift, and address explainability, fairness, bias, and performance issues.
• Contribute to the evolution of enterprise AI/ML platforms by creating reusable components, accelerators, and governance workflows.
• Build operational dashboards and metrics to ensure reliable AI system performance and compliance.
• Collaborate closely with data scientists, engineers, product teams, and business stakeholders to deliver scalable AI solutions.
• Continuously assess new AI/ML technologies and integrate best practices into platform development.

Required Qualifications & Experience

• 3 to 10 years of experience in machine learning engineering, AI platform development, or MLOps roles.
• Proven track record of developing and deploying production-grade ML solutions.
• Hands-on expertise with the full ML lifecycle: data engineering, feature engineering, model training, deployment, and monitoring.
• Experience building scalable AI applications and ML APIs.
• Strong knowledge of MLOps methodologies such as CI/CD pipelines, experiment tracking, versioning, and automated retraining.
• Familiarity with deploying ML models on cloud platforms and production environments.
• Understanding of responsible AI including model governance, explainability, fairness, and bias mitigation.
• Solid grasp of scalable software engineering concepts and distributed machine learning systems.

Technical Skills

• Machine Learning frameworks and libraries: Scikit-learn, XGBoost, LightGBM, CatBoost, TensorFlow, PyTorch
• Data engineering: SQL, PySpark, Apache Spark, Databricks, Airflow, BigQuery
• MLOps tools: MLflow, Kubeflow, SageMaker, Vertex AI, Azure Machine Learning, Databricks
• Programming: Python, FastAPI, Flask, REST API development
• Cloud platforms: Microsoft Azure, Amazon Web Services (AWS), Google Cloud Platform (GCP)
• Containers and DevOps: Docker, Kubernetes, Terraform, GitHub Actions, Jenkins

Preferred Experience

• Building enterprise-scale AI products and intelligent business applications.
• Experience with complete AI/ML platforms and architectures.
• Knowledge of LLMOps and deployment of generative AI solutions.
• Understanding of feature stores, model registries, and metadata management systems.
• Proficiency in deploying scalable, distributed machine learning systems in production.
• Familiarity with AI governance frameworks, model observability, and cloud-native ML infrastructure.

Educational Background

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering or related disciplines.

Soft Skills

• Strong analytical thinking and problem-solving capabilities.
• Excellent verbal and written communication along with collaboration skills.
• Adept at working within cross-functional agile teams.
• Demonstrates ownership and accountability to deliver scalable AI solutions.
• Committed to innovation and ongoing learning in AI technologies.
• Capable of managing multiple priorities in a dynamic environment.
• Attention to detail with focus on quality, system performance, and business impact.