ML Engineer – Customer Data & Analytics

Work Location: Bangalore

About Us

We are growing our Data & AI practice, which delivers cloud data platforms, data modernisation and migration, analytics and AI-enabled engineering for global enterprise clients. You will work in cross-functional teams on long-term engagements, using modern cloud technologies and AI-assisted engineering practices. Location: Offshore (India) · Full-time.

Role Summary

Builds and runs production ML on customer data – identity resolution, propensity and scoring models – with MLOps discipline.

Experience

Level

Total experience

Relevant experience (must)

ML Engineer

6–10 years

3+ years applied ML / entity resolution; 2+ years production ML on AWS

Roles & Responsibilities

• Build identity resolution / record matching (deterministic and probabilistic)
• Develop propensity, engagement and scoring models
• Productionise models as batch pipelines; set up registry, monitoring and retraining
• Measure model quality (precision / recall, drift) and explain results to business
• Work with data engineers on features, performance and cost

Mandatory Skills

• Python, PySpark, statistics
• Entity resolution tools (Splink, Zingg, AWS Entity Resolution or equivalent)
• ML on AWS (SageMaker or Spark ML)
• MLOps tooling (MLflow or equivalent)

Nice to Have

• Marketing analytics / lead scoring
• MDM
• Feature stores
• GenAI / LLM applications

Also Expected

Clear communication with remote client stakeholders across time zones; Comfortable using AI coding and productivity tools, and reviewing AI-generated work critically; Agile ways of working; ownership and accountability. Certifications: AWS Certified Machine Learning Engineer / Specialty (plus).