Job Description

Job Title- Machine Learning Engineer

Location- Pune | Hybrid

Experience- 6–8 Years

Primary Skills- Python, SQL, Machine Learning, ML Modelling, Agentic AI

About The Role

We are building AI-powered solutions that help businesses improve customer outcomes, operational efficiency, revenue growth, and decision-making through the practical application of Machine Learning and AI.

As part of the AI Engineering team, you will work on the design, development, deployment, and optimization of ML-driven solutions that deliver measurable business value across customer-facing and operational workflows.

Roles And Responsibilities

Machine Learning Solution Development

- Design, develop, and deploy Machine Learning models for prediction, recommendation, optimization, classification, and forecasting use cases.
- Build scalable ML pipelines covering data preparation, feature engineering, model training, evaluation, and deployment.
- Apply statistical and machine learning techniques to solve business problems using structured and semi-structured data.
- Collaborate with Product, Engineering, and Business teams to translate requirements into production-ready AI/ML solutions.

Data Engineering & Integration

- Build and maintain data pipelines to ingest, transform, and process data from enterprise systems, APIs, databases, and external sources.
- Develop reusable data services and ML components to accelerate solution delivery.
- Ensure data quality, reliability, and scalability for model development and production workloads.

MLOps & Productionization

- Implement CI/CD pipelines for ML models and AI services.
- Establish model monitoring, performance tracking, retraining, and deployment processes.
- Manage model lifecycle, experimentation, versioning, and governance.
- Support deployment of AI/ML workloads on AWS or Azure cloud platforms.

Engineering Excellence

- Follow best practices for software engineering, testing, observability, and documentation.




- Leverage AI-assisted development tools to improve engineering productivity.
- Contribute to reusable frameworks, engineering standards, and best practices across the AI team.

Qualifications & Required Skills

- 6–8 years of software engineering experience with strong Python development skills.
- 3+ years of hands-on experience building and deploying Machine Learning solutions.
- Experience building Agentic AI solutions using LangGraph, LangChain, AutoGen, CrewAI, or similar frameworks.
- Strong understanding of supervised and unsupervised learning techniques.
- Experience with recommendation systems, predictive analytics, forecasting, classification, anomaly detection, or optimization.
- Hands-on experience with Scikit-Learn, XGBoost, LightGBM, TensorFlow, PyTorch, or equivalent ML frameworks.
- Strong SQL and data analysis skills.
- Experience with feature engineering, model evaluation, and experimentation.
- Familiarity with MLOps, model deployment, monitoring, and lifecycle management.
- Experience building data pipelines and integrating enterprise systems through APIs and databases.
- Experience with Docker, CI/CD, Git, and contemporary software engineering practices.
- Experience working with AWS or Azure.
- Strong analytical, problem-solving, and communication skills.

Mandatory Skills

- Python
- SQL
- Machine Learning / ML Modelling
- Agentic AI
- LangGraph / LangChain / AutoGen / CrewAI
- Scikit-Learn / XGBoost / LightGBM / TensorFlow / PyTorch
- Feature Engineering & Model Evaluation
- ML Pipelines & Data Engineering
- MLOps & Model Deployment
- Docker & CI/CD
- Git
- AWS / Azure

Good To Have Skills





Advanced AI & Data

- Optimization techniques, routing algorithms, scheduling, or Operations Research.
- Demand forecasting, customer propensity modeling, pricing analytics, and recommendation engines.
- Explainable AI, model evaluation frameworks, and experimentation methodologies.
- Snowflake, Databricks, or modern cloud data platforms.
- Large-scale data processing and distributed computing.
- Analytical dashboards and decision-support solutions.

Generative AI

- LLMs, RAG architectures, vector databases, and agentic frameworks.
- Integration of ML solutions with GenAI applications.

Domain Knowledge

- Sales, pricing, customer intelligence, e-commerce, distribution, logistics, supply chain, or ERP/CRM ecosystems.

TECHNOLOGY STACK

- Languages: Python, SQL
- ML Frameworks: Scikit-Learn, XGBoost, LightGBM, TensorFlow, PyTorch
- Agentic AI: LangGraph, LangChain, AutoGen, CrewAI
- Data: Snowflake, SQL, APIs, Data Pipelines
- MLOps: MLflow, Docker, CI/CD, Model Monitoring
- Cloud: AWS / Azure
- Development Tools: GitHub, Azure DevOps, GitLab, GitHub Copilot, Cursor

About Sonata Software

Sonata Software is an AI-first modernization engineering company that helps enterprises transform legacy systems into intelligent, scalable business platforms. Powered by its Platformation™ framework and Harmoni.AI platform, Sonata delivers AI-led modernization across cloud, data, AI, Dynamics, test automation, and managed services. Headquartered in Bengaluru, India, Sonata has more than $1.2 billion in revenue and 6,400+ AI engineers supporting global delivery across regions including the US, UK, India, Malaysia, Mexico, Australia, DACH, and the Nordics. With deep partnerships across Microsoft, AWS, Salesforce, and Snowflake, Sonata helps Fortune 500 enterprises accelerate innovation, improve efficiency, and drive sustainable growth. For more information, please visit www.sonata-software.com .

📌 Machine Learning Engineer (Pune)
🏢 Sonata Software
📍 Pune