Python / ML Engineer

Job Description (JD) Python / Machine Learning Engineer (Hands-On)

Position: Python / Machine Learning Engineer
Experience: 8-15 years Years (adjustable)
Location: Bangalore ( WFO)
Employment Type: Full-Time

Role Summary

We are looking for a highly skilled and hands-on Python / Machine Learning Engineer to design, develop, deploy, and optimize machine learning solutions. The ideal candidate should have strong Python programming expertise, experience building end-to-end ML pipelines, and the ability to work closely with business stakeholders, data scientists, and engineering teams.

Key Responsibilities

• Design, develop, and maintain scalable ML and AI solutions.
• Build and optimize data pipelines for model training and inference.
• Develop and deploy machine learning models in production environments.
• Implement model monitoring, performance tuning, and retraining strategies.
• Write clean, efficient, and reusable Python code following best practices.
• Work with structured and unstructured datasets for feature engineering and model development.
• Integrate ML services with APIs, applications, and cloud platforms.
• Collaborate with cross-functional teams to translate business requirements into technical solutions.
• Conduct model evaluation, validation, and experimentation.
• Stay updated with emerging AI/ML technologies and industry trends.

Required Skills

Programming

• Strong hands-on experience in Python
• Solid understanding of OOP, data structures, algorithms, and design patterns
• Experience with REST APIs and microservices

Machine Learning

• Hands-on experience with:

• Scikit-learn

• XGBoost/LightGBM

• TensorFlow or PyTorch

• Strong understanding of:

• Supervised & Unsupervised Learning

• Classification & Regression

• Clustering

• Feature Engineering

• Model Evaluation Techniques

Data Engineering

• Pandas, NumPy
• SQL and database optimization
• Experience with ETL pipelines
• Exposure to Spark/PySpark is preferred

MLOps & Deployment

• Docker, Kubernetes
• MLflow, Kubeflow, or similar tools
• CI/CD pipelines
• Model deployment and monitoring

Cloud Platforms

• AWS / Azure / GCP
• Experience with cloud-native ML services is desirable

Good to Have

• Experience with Generative AI / LLMs
• LangChain, LlamaIndex, RAG architectures
• Vector databases (Pinecone, FAISS, ChromaDB, Weaviate)
• Prompt engineering and LLM evaluation
• NLP, Computer Vision, or Deep Learning projects
• Experience with Azure OpenAI or OpenAI APIs

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or related field.
• Proven experience building and deploying production-grade ML solutions.
• Strong problem-solving and analytical skills.

Excellent communication and stakeholder-management abilities