Senior AI/ML Engineer - Platform
A.P. Moller - Maersk (company site, opens in a new tab)BengaluruOn-siteDirect career pageEst. 30–55 LPA
Posted on 22 Sept
Reach people at A.P. Moller - Maersk
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at A.P. Moller - Maersk you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Design, implement, and maintain scalable end-to-end machine learning solutions, including feature engineering, model deployment, and monitoring for production environments.
- Collaborate with stakeholders to translate business needs into integrated data engineering and AI/ML platform solutions, ensuring reliability and value-driven delivery.
- Lead cross-team initiatives to optimize workflows, share best practices, and mentor team members through code reviews and knowledge sharing to improve AI/ML platform capabilities.
Minimum Requirements
- Proficient programming skills in Python, R, and SQL.
- Advanced proficiency in building and deploying machine learning pipelines and models in production.
- Experience working with big data technologies and data processing frameworks like Apache Hadoop and Apache Spark.
- Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
- Experienced in AI/ML platform engineering combining cloud infrastructure, software engineering, DevOps, and MLOps for enterprise AI solutions.
- Has a strong background implementing scalable AI/ML workflows, emphasizing model lifecycle management, monitoring, observability, and governance.
- Able to communicate technical concepts clearly to both technical and non-technical stakeholders and drive cross-functional collaboration.