Senior ML Engineer

Job Description :

Python / Machine Learning Engineer (Hands-On)

Position : Python / Machine Learning Engineer

Experience : 8-15 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 :

1. Programming :

- Strong hands-on experience in Python

- Solid understanding of OOP, data structures, algorithms, and design patterns

- Experience with REST APIs and microservices

2. 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

3. Data Engineering :

- Pandas, NumPy

- SQL and database optimization

- Experience with ETL pipelines

- Exposure to Spark/PySpark is preferred

4. MLOps & Deployment :

- Docker, Kubernetes

- MLflow, Kubeflow, or similar tools

- CI/CD pipelines

- Model deployment and monitoring

5. 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.

Skills

Machine Learning, Python, Pandas, Numpy, Data Structure, Algorithm, Design Patterns, REST API, Generative AI