Applied Artificial Intelligence and Machine Learning Associate

JP Morgan Services India Pvt Ltd; Bengaluru; On-site; INR 2,500,000 - 4,000,000; Full time

Job summary

JPMorganChase in Bengaluru, India, is seeking an Applied AI ML Associate to design, deploy, and productionize agent-based AI solutions that turn business needs into measurable outcomes.

You will collaborate with engineers and data professionals to build end-to-end ML pipelines, evaluate language models, and implement human-in-the-loop workflows, with mentorship and growth opportunities.

Qualifications

• Master’s degree or higher in Computer Science, Data Science, or related field.
• 3+ years of industry experience with at least 2 years in ML engineering/data science.
• Experience applying ML methods (regression, classification, clustering, time series).
• Hands-on with agent-based solutions and tool integrations using agent frameworks (Google ADK, LangGraph).
• Proficient in Python for production development.
• Experience building data pipelines; PySpark knowledge beneficial.
• Knowledge of deep learning frameworks (TF or PyTorch) and NLP techniques.
• Strong communication across engineering and business teams.

Responsibilities

• Design and deliver agent-based AI solutions from prototype to production.
• Implement human-in-the-loop workflows and tool-calling patterns to improve reliability.
• Evaluate language models with metrics, experiments, and documentation.
• Build reusable AI tools connecting models to enterprise data and services.
• Develop end-to-end ML pipelines for data prep, training, validation, and deployment.
• Apply retrieval-augmented generation to improve accuracy and grounding.
• Use deep learning for semantic search, entity resolution, forecasting, and anomaly detection.
• Own small-to-medium engineering deliverables across lifecycle stages.
• Collaborate with cross-functional teams to translate findings into improvements.
• Incorporate governance and risk considerations for safe ML use.

Skills

Master’s degree in CS/Data Science

ML engineer

Python

PySpark

TensorFlow

PyTorch

NLP

Agent frameworks

LangGraph

Google ADK

Education

Master’s degree or higher in Computer Science, Data Science, or related

Tools

TensorFlow

PyTorch

Job description

Applied AI ML Associate Make your mark by building agentic artificial intelligence solutions that turn complex business needs into measurable outcomes. Join a collaborative engineering team where you will design, deploy, and improve production-grade machine learning systems using modern large language model techniques. Grow your career through high-impact work, strong mentorship, and opportunities to expand your technical depth and product delivery skills. As an Applied AI ML Associate in JPMorgan Chase, you design and deliver secure, stable, and scalable technology products using machine learning. You build and productionize agent-based solutions and data-driven systems that solve real business problems. You partner with engineers, data professionals, and stakeholders to define requirements, evaluate approaches, and deliver measurable improvements. You apply strong software engineering practices to testing, release, and support.

Job Responsibilities

• Design and deliver agent-based artificial intelligence solutions that address defined business use cases from prototype through production deployment.
• Implement human-in-the-loop workflows, fallback behaviors, and tool-calling patterns to improve reliability, traceability, and user outcomes.
• Evaluate candidate language models for specific use cases by defining metrics, running experiments, and documenting performance, limitations, and trade-offs.
• Build reusable artificial intelligence tools and integrations that connect models and agents to enterprise data and services.
• Develop end-to-end machine learning pipelines that prepare data, train or adapt models, validate quality, and support repeatable deployments.
• Apply retrieval-augmented generation methods to improve answer accuracy and grounding on large datasets.
• Use deep learning techniques (including attention-based architectures) to support solutions such as semantic search, entity resolution, forecasting, and anomaly detection where appropriate.
• Own small-to-medium engineering deliverables end-to-end, including requirements clarification, design, implementation, testing, release, and post-release support.
• Collaborate with cross-functional partners to establish baselines, analyze results, and translate findings into actionable improvements.
• Incorporate governance, risk, and control considerations into solution design and delivery to support safe and responsible use of machine learning capabilities.

Required qualifications, capabilities, and skills

• Master’s degree or higher in Computer Science, Data Science, or a related discipline (or equivalent).
• 3+ years of industry experience, including a minimum of 2 years hands‑on experience as a machine learning engineer, data engineer, or data scientist.
• Demonstrated experience applying machine learning methods such as regression, classification, clustering, time series modeling, causal inference, or mathematical optimization.
• Hands‑on experience designing and building agent-based solutions and tool integrations using agent frameworks (for example, Google ADK, LangGraph) and agent‑to‑agent communication patterns.
• Proficiency in Python for production‑oriented development (testing, packaging, and deployment practices).
• Hands‑on experience building data pipelines and working with large datasets; experience with PySpark is acceptable where relevant.
• Working knowledge of deep learning frameworks (TensorFlow or PyTorch) and modern natural language processing techniques.
• Strong written and verbal communication skills with experience partnering with stakeholders across engineering and business functions.

Preferred qualifications, capabilities, and skills

• Experience building multi‑agent solutions in enterprise environments.
• Experience leading data science or machine learning workstreams end‑to‑end (problem framing, experimentation, deployment, measurement).
• Experience designing large‑scale machine learning systems (latency, cost, monitoring, and reliability considerations).
• Experience with cloud-based machine learning services and production pipelines.
• Experience with the Amazon Web Services machine learning ecosystem.
• Experience optimizing model training or inference using graphics processing units where required.
• Familiarity with transformer‑based embedding models (for example, BERT, Sentence‑BERT) and prompt optimization techniques.

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

Experience Level Mid Level