Job Description

NOTE: This is Fulltime Role with Infotech Global Pvt Ltd and its 100% Onsite Role as the working Location is Pune.

Key responsibilities

Translate business questions into analytic approaches and machine learning solutions. Design and implement end-to-end ML pipelines: data ingestion, feature engineering, model training, validation, deployment and monitoring. Develop, validate and productionize supervised and unsupervised models (classification, regression, ranking, time series, clustering). Implement model evaluation, A/B testing and performance monitoring; iterate based on results. Apply explainability, fairness and privacy-aware practices to model development, document assumptions and limitations. Collaborate with software engineering to containerize and deploy models (Docker, Kubernetes) and integrate with APIs or event-driven systems. Automate CI/CD for ML and analytics workflows; manage model versioning and reproducibility. Create clear technical documentation and present findings and recommendations to technical and non-technical stakeholders. Stay current with AI/ML trends and evaluate new tools and frameworks for improved outcomes.

Required qualifications

3+ years of experience developing machine learning models and analytics solutions in a commercial environment (or equivalent experience). Strong programming skills in Python and familiarity with ML libraries such as TensorFlow. Experience with cloud platforms (AWS, GCP, or Azure) and at least one managed ML/data service or managed LLM offering Experience with model deployment and MLOps practices (Docker, Kubernetes, model serving frameworks, CI/CD, and GitOps tooling like ArgoCD). Strong foundational knowledge in machine learning, including linear and logistic regression, support vector machines, decision trees, and neural networks. Good statistical grounding: hypothesis testing, experimental design, evaluation metrics. Strong communication skills; ability to explain technical concepts to business partners and influence decisions.

Strong preference:

Demonstrable experience deploying LLMs and building RAG pipelines in production. Experience with cloud-managed LLM services (Vertex AI, SageMaker, Azure OpenAI) - GCP familiarity is a plus. Experience with LangChain, LangGraph, or similar agent frameworks to build multi-agent workflows Familiarity with MCP or stateful context management patterns for multi-agent systems.

Preferred qualifications

Master's or advanced degree in Computer Science, Data Science, Statistics, Engineering, Mathematics or related field. Background in explainable AI, model risk management or regulated environments (finance, payments). Familiarity with observability tools for ML (Prometheus, Grafana, Seldon, Fiddler, Evidently, etc.). Experience implementing privacy-preserving ML techniques and working with secure data environments.
Job Type: Full-time

Pay: ₹2,000,000.00 - ₹3,500,000.00 per year

Benefits:

Health insurance Paid time off Provident Fund
Work Location: In person