ML (Data) Platform Engineer

This role is for one of the Weekday's clients

Min Experience: 5 years

Location: Remote (India), Bengaluru, Chennai

JobType: full-time

We are seeking a skilled ML (Data) Platform Engineer to help scale a next-generation AutoML platform. This role sits at the critical intersection of machine learning, data infrastructure, and platform engineering. You will work on systems central to feature engineering, data management, and time series forecasting at scale.

This is not your typical ETL role — the position involves building powerful data platforms that support automated model development, experimentation workflows, and high-reliability data lineage systems. If you're passionate about building scalable systems for both ML and analytics use cases, this is a high-impact opportunity.

Requirements

Key Responsibilities:

• Design, build, and scale robust data management systems that power AutoML and forecasting platforms.
• Own and enhance feature stores and associated engineering workflows.
• Establish and enforce strong data SLAs and build lineage systems for time series pipelines.
• Collaborate closely with ML engineers, infrastructure, and product teams to ensure platform scalability and usability.
• Drive key architectural decisions related to data versioning, distribution, and system composability.
• Contribute to designing reusable platforms to address diverse supply chain challenges.

Must-Have Qualifications:

• Strong experience with large-scale and distributed data systems.
• Hands-on expertise in ETL workflows, data lineage, and reliability tooling.
• Solid understanding of ML feature engineering and experience building or maintaining feature stores.
• Exposure to time series forecasting systems or AutoML platforms.
• Strong analytical and problem-solving skills, with the ability to deconstruct complex platform requirements.

Good-to-Have Qualifications:

• Familiarity with modern data infrastructure tools such as Apache Iceberg, ClickHouse, or Data Lakes.
• Product-oriented mindset with an ability to anticipate user needs and build intuitive systems.
• Experience with building composable, extensible platform components.
• Previous exposure to AutoML frameworks such as SageMaker, Vertex AI, or equivalent internal ML platforms.

Skills:
MLOps, Data Engineering, Big Data, ETL, Feature Store, Feature Engineering, AutoML, Forecasting Pipelines, Data Management