AI/ML Engineer

Job Title : AI/ML Engineer

Location: Pune | Hybrid

Experience: 6–8 Years

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

About The Role We are looking for an experienced AI/ML Engineer to join our AI Engineering team and build intelligent, scalable, and production-ready AI/ML solutions.

The role will focus on designing, developing, deploying, and optimizing Machine Learning models and Agentic AI solutions that deliver measurable business value across customer-facing and operational workflows.

The ideal candidate should have strong hands-on experience in Python, Machine Learning, SQL, MLOps, and Agentic AI frameworks , along with the ability to translate business requirements into scalable AI solutions.

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 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.
• Work closely with product, engineering, and business teams to translate requirements into production-ready AI/ML solutions.

Agentic AI Development

• Design and develop agentic workflows using frameworks such as LangGraph, LangChain, AutoGen, CrewAI, or similar.
• Develop AI agents capable of reasoning, task orchestration, tool usage, and multi-step workflow execution.
• Integrate AI agents with enterprise systems, APIs, databases, and business applications.
• Combine Agentic AI capabilities with predictive and analytical ML models.

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 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.
• Hands-on 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 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 enterprise systems through APIs and databases.
• Experience with Docker, CI/CD, 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 modelling, pricing analytics, and recommendation engines.
• Experience with explainable AI, model evaluation frameworks, and experimentation methodologies.

Data & Analytics

• 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 AI frameworks.
• Experience integrating ML solutions with Generative AI applications.

Domain Knowledge Exposure to Sales, Pricing, Customer Intelligence, E-commerce, Distribution, Logistics, Supply Chain, or ERP/CRM ecosystems is preferred.

Technology Stack Area Technologies Programming Python, SQL

ML Frameworks Scikit-Learn, XGBoost, LightGBM, TensorFlow, PyTorch

Agentic AI LangGraph, LangChain, AutoGen, CrewAI

Generative AI LLMs, RAG, Vector Databases

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.

Website: www.sonata-software.com m