ML Engineer-5+Yrs-PAN INDIA

Job Summary

We are looking for a highly skilled Machine Learning Engineer with strong expertise in developing, deploying, and optimising machine learning models at scale. The ideal candidate should have hands-on experience in Python, ML frameworks, feature engineering, model deployment, and MLOps. Exposure to Generative AI and Large Language Models (LLMs) is preferred.

Mandatory Skills

• Python
• Machine Learning Algorithms
• Scikit-Learn
• Pandas, NumPy
• TensorFlow or PyTorch
• Data Preprocessing & Feature Engineering
• Model Training & Evaluation
• SQL
• API Development (FastAPI/Flask)
• Git
• Cloud Platforms (AWS/Azure/GCP)

Good to Have

• Generative AI & LLMs
• LangChain / LangGraph
• RAG Architecture
• Vector Databases (Pinecone, ChromaDB, FAISS)
• MLOps (MLflow, Kubeflow)
• Databricks
• Spark / PySpark
• Docker & Kubernetes
• NLP or Computer Vision

Key Responsibilities

• Design, develop, and deploy machine learning models for business use cases.
• Build scalable ML pipelines for data ingestion, transformation, training, and inference.
• Perform feature engineering, model selection, tuning, and validation.
• Deploy and monitor models in production environments.
• Collaborate with data scientists, data engineers, and business stakeholders.
• Implement MLOps best practices for model versioning, monitoring, and retraining.
• Optimize model performance, accuracy, and scalability.
• Create APIs and services to integrate ML models with enterprise applications.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or related field.
• 4+ years of experience in Machine Learning and Python development.
• Strong understanding of supervised and unsupervised learning techniques.
• Hands-on experience with TensorFlow, PyTorch, or Scikit-Learn.
• Experience deploying ML models into production environments.
• Strong understanding of statistics, probability, and data structures.
• Excellent analytical and problem-solving skills.

Preferred Experience

• Experience with recommendation systems, forecasting, NLP, or Computer Vision.
• Exposure to Generative AI applications and LLM integration.
• Experience with cloud-native ML deployments.
• Familiarity with CI/CD and MLOps frameworks.

TA Screening Keywords

Machine Learning, Python, Scikit-Learn, TensorFlow, PyTorch, Pandas, NumPy, Feature Engineering, Model Deployment, MLOps, MLflow, FastAPI, Flask, AWS, Azure, GCP, NLP, Computer Vision, GenAI, LLM, LangChain.

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