Applied AI ML Associate
Skills
About the role
This is a mid-level applied AI/ML engineering role at JPMorganChase in Bengaluru, building production agentic AI and machine learning systems for the firm's Commercial & Investment Bank. It suits someone who has already shipped ML systems and wants to move into agent-based, LLM-driven production work. You'll design and deploy agent workflows, retrieval-augmented generation systems and data pipelines while working closely with engineering and business stakeholders.
What you’ll do
- Design and deliver agent-based AI solutions from prototype through production.
- Implement human-in-the-loop workflows, fallback behaviors and tool-calling patterns.
- Evaluate candidate language models against defined metrics and document trade-offs.
- Build reusable AI tools and integrations connecting models to enterprise data.
- Develop end-to-end ML pipelines covering data prep, training, validation and deployment.
- Apply retrieval-augmented generation to improve grounding and accuracy.
- Use deep learning techniques for tasks like semantic search, entity resolution and forecasting.
- Own small-to-medium deliverables end-to-end including testing and post-release support.
- Incorporate governance, risk and control considerations into solution design.
What they’re looking for
- Master's degree or higher in Computer Science, Data Science or a related field.
- 3+ years of industry experience, including at least 2 years hands-on as an ML engineer, data engineer or data scientist.
- Experience applying ML methods such as regression, classification, clustering, time series or optimization.
- Hands-on experience building agent-based solutions with frameworks like Google ADK or LangGraph.
- Proficiency in Python for production-oriented development.
- Experience building data pipelines and working with large datasets.
- Working knowledge of TensorFlow or PyTorch and modern NLP techniques.
- Strong written and verbal communication skills.
Nice to have
- Experience building multi-agent solutions in enterprise environments.
- Experience leading data science or ML workstreams end-to-end.
- Experience designing large-scale ML systems for latency, cost and reliability.
- Experience with cloud-based ML services and the AWS ML ecosystem.
- Experience optimizing training or inference on GPUs.
- Familiarity with transformer-based embedding models and prompt optimization.
Questions about this role
Is this role remote?
No, it's hybrid, based in Bengaluru.
How many years of experience do I need?
3+ years of industry experience, including at least 2 years hands-on as an ML engineer, data engineer or data scientist.
Do I need a degree?
A Master's degree or higher in Computer Science, Data Science or a related field is required.
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