Machine Learning Engineer – AI/ML

Title: Machine Learning Engineer Location: Gurgaon, Haryana (Onsite/Hybrid) Experience:

• 4-6 years of hands-on experience in Machine Learning Engineering, Applied Machine Learning, or related roles.
• Experience with Pandas, NumPy, Scikit-learn, and related Python libraries.
• Hands-on experience with Large Language Models (LLMs).
• Strong proficiency in Python. About the Role: We are seeking a highly motivated Machine Learning Engineer with 4–6 years of experience to design, build, deploy, and optimize scalable machine learning solutions that solve real-world business problems. The ideal candidate has hands-on experience in developing production-grade ML models, implementing MLOps best practices, and collaborating with cross-functional teams to deliver AI-driven products. Key Responsibilities: Machine Learning Development:
• Design, develop, train, and optimize Machine Learning and Deep Learning models for classification, regression, forecasting, NLP, and computer vision applications.
• Perform feature engineering, model selection, hyperparameter tuning, and performance evaluation.
• Conduct experiments and improve model accuracy, scalability, and reliability. Model Deployment & MLOps:
• Deploy, monitor, and maintain ML models in production environments.
• Build and manage end-to-end ML pipelines using MLOps best practices.
• Implement CI/CD workflows for machine learning applications.
• Containerize applications using Docker and orchestrate deployments with Kubernetes. Data Engineering & Processing:
• Work with structured and unstructured datasets to build scalable data pipelines.
• Process and analyze large datasets using SQL and distributed data processing tools.
• Collaborate with data engineering teams to ensure high-quality data availability. Cross-functional Collaboration:
• Partner with Data Scientists, Product Managers, Backend Engineers, and Business stakeholders to understand requirements and deliver ML-powered solutions.
• Translate business challenges into scalable machine learning applications. Model Monitoring & Optimization:
• Monitor model performance, latency, drift, and reliability in production.
• Continuously improve deployed models through retraining and optimization.
• Implement logging, monitoring, and alerting mechanisms for ML systems. Research & Innovation:
• Stay updated with the latest advancements in Machine Learning, Deep Learning, Generative AI, and MLOps.
• Evaluate and integrate new frameworks, tools, and best practices into existing workflows. Required Skills & Experience:
• 4-6 years of hands-on experience in Machine Learning Engineering, Applied Machine Learning, or related roles.
• Strong proficiency in Python .
• experience with Pandas, NumPy, Scikit-learn , and related Python libraries.
• Hands-on experience with: TensorFlow, PyTorch, Keras, XGBoost.
• Practical experience with one or more cloud platforms: AWS, Google Cloud Platform (GCP), Microsoft Azure
• Experience with Amazon SageMaker , Vertex AI , or Azure Machine Learning is an added advantage.
• Experience with: Docker, Kubernetes, FastAPI or Flask, CI/CD pipelines for ML applications, Model versioning and deployment strategies.
• Strong knowledge of SQL and NoSQL databases.
• Familiarity with Apache Spark and Hadoop is preferred.
• Experience processing large-scale datasets. Preferred Skills:
• Hands-on experience with Large Language Models (LLMs).
• Experience using LangChain , LlamaIndex , or similar orchestration frameworks.
• Knowledge of Vector Databases such as Pinecone , Weaviate , or Milvus .
• Experience in NLP, Computer Vision, Recommendation Systems, or Generative AI applications.
• Familiarity with experimentation frameworks, A/B testing, and model evaluation methodologies. Educational Qualification:
• Bachelor's or Master's degree (B.Tech/M.Tech) in Computer Science, Artificial Intelligence, Data Science, Information Technology, or a related field.