2 hours ago
Bengaluru, IndiaMid Level
Responsibilities
- Assist in designing, developing, deploying, and maintaining machine learning and AI solutions for supply chain challenges.
- Contribute to ML pipelines for forecasting, optimization, predictive analytics, anomaly detection, and intelligent automation.
- Support the design, testing, and deployment of AI agents and multi-agent systems using LangGraph, LangChain, AutoGen, CrewAI, or similar frameworks.
- Develop intelligent workflows using LLMs, tool integration, memory, and orchestration to automate business processes.
- Help build data ingestion, transformation, feature engineering, knowledge integration, vector database, and intelligent document processing pipelines.
- Assist with AI and ML deployment on AWS and Microsoft Azure, including MLOps and LLMOps pipelines, model versioning, automated deployment, monitoring, and retraining.
- Evaluate and monitor ML models and LLMs, improve accuracy and inference latency, optimize cloud resources, and support responsible AI practices.
- Collaborate with supply chain stakeholders, data scientists, software engineers, cloud architects, product managers, and transformation teams; participate in code reviews and technical documentation.
Requirements
- Bachelor’s degree in computer science, software engineering, AI, or a related field with 2–4 years of professional experience, or a master’s degree with relevant industry experience and 2–3 years of experience including internship experience.
- At least 3 years of hands-on Python experience and foundational knowledge of designing, developing, and supporting ML and AI solutions.
- Experience or exposure to predictive modeling, forecasting, feature engineering, model evaluation, and cloud platforms such as Azure, Databricks, or AWS.
- Exposure to or coursework/project experience with generative AI applications and agentic AI workflows.
- Foundational understanding of LLMs, prompt engineering, RAG, AI evaluation techniques, and responsible AI practices.
- Basic understanding of system design patterns, microservices architecture, APIs, Docker, Kubernetes, and infrastructure automation.
- Familiarity with or willingness to learn AI observability and evaluation tools including Azure AI Foundry, Azure Monitor, Azure ML Monitoring, AWS CloudWatch, MLflow, LangSmith, Prometheus, Grafana, and OpenTelemetry.
- Exposure to enterprise data platforms, data pipelines, SQL, and distributed data processing frameworks.
- Preferred academic, internship, or project experience applying AI/ML to supply chain, retail, healthcare, or other enterprise domains.
Benefits
- Hybrid role located in Bangalore with 40% commuting to the office.