Senior Digital Engineer

Job Title :AI/ML Engineer

Location: Pune | Hybrid

Experience: 6-8 years

Primary Skill: Python, SQL, ML Modelling, Agentic AI

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

Our Objective

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.

Key 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 for 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.
• Work closely 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 and ML workloads on 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, standards, and best practices across the AI team.

Required Qualifications

• 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 frameworks such as LangGraph, LangChain, AutoGen, CrewAI, or similar.
• Strong understanding of supervised and unsupervised learning techniques.
• Experience with recommendation systems, predictive analytics, forecasting, classification, anomaly detection, or optimization problems.
• 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 frameworks.
• Familiarity with MLOps practices, model deployment, monitoring, and lifecycle management.
• Experience building data pipelines and integrating with enterprise systems through APIs and databases.
• Experience with Docker, CI/CD pipelines, Git, and modern software engineering practices.
• Experience working with AWS or Azure cloud platforms.
• Strong analytical, problem-solving, and communication skills.

Good to Have Advanced AI & Data Platforms

• Experience with optimization techniques, routing algorithms, scheduling, or Operations Research.
• Knowledge of demand forecasting, customer propensity modeling, pricing analytics, and recommendation engines.
• Experience with explainable AI, model evaluation frameworks, and experimentation methodologies.

Data & Analytics

• Knowledge of Operations Research, routing algorithms, scheduling, or decision optimization techniques.
• Experience with demand forecasting, pricing analytics, customer intelligence, propensity modeling, and recommendation engines.
• Experience with Snowflake, Databricks, or modern cloud data platforms.
• Experience building analytical dashboards and decision-support solutions.
• Familiarity with large-scale data processing and distributed computing.

Generative AI

• Exposure to LLMs, RAG architectures, vector databases, and agentic frameworks.
• Experience integrating ML solutions with GenAI applications.

Domain Knowledge

• Exposure to 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 or Azure
• Development Tools: GitHub, Azure DevOps, GitLab, GitHub Copilot, Cursor