ML Engineer – Customer Data & Analytics
Impelsys (company site, opens in a new tab)6–10 yrsBengaluruOn-siteDirect career pageEst. 18–35 LPA
Posted 21h ago
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Job description
Structured overview of role & requirements
About This Role
- Develop and productionise ML models for identity resolution, propensity, engagement and scoring using AWS-based MLOps pipelines.
- Implement and manage batch pipelines with model registry, monitoring for quality including precision/recall and drift, plus retraining workflows.
- Collaborate with data engineers to optimize features, performance, and cost while explaining model outcomes to business stakeholders.
Minimum Requirements
- 6–10 years total experience with at least 3 years in applied ML related to entity resolution and 2+ years in production ML on AWS.
- Proficiency in Python, PySpark, statistics, and entity resolution tools (e.g., Splink, Zingg, AWS Entity Resolution).
- Experience with ML on AWS platforms (SageMaker or Spark ML) and MLOps tooling (MLflow or equivalent).
- Location: Bangalore, India (Offshore role); Work Experience Required: 6-10 years; Certifications AWS ML Specialty: Nice to have but not mandatory.
Ideal Candidate Profile
- Experienced ML Engineer comfortable managing end-to-end ML lifecycle in a cloud (AWS) environment with strong MLOps discipline.
- Hands-on expertise with identity resolution and record matching in production systems, able to measure and communicate model effectiveness via metrics like precision/recall and drift.
- Skilled in collaborating with remote, cross-functional teams and working with data engineers to balance feature development, system performance and cost.