Machine Learning Engineer

Sony India Software Centre

1 - 4 years

11 - 12 Lacs

nagercoil

Posted:-1 days ago| Platform:

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Skills Required

it services system architecture deep learning compliance gcp it consulting machine learning architectural design deployment monitoring

Work Mode

Work from Office

Job Type

Full Time

Job Description

We are seeking a highly experienced and results-oriented Machine Learning Engineer to join our AI/ML Center of Excellence (CoE). As a leader in IT consulting and services, we need skilled engineers to design, build, and productionize robust, scalable, and secure ML and Generative AI solutions for our enterprise clients. This role involves engineering the full MLOps lifecycle, from initial research and prototyping to large-scale deployment and continuous monitoring.
Designing, building, and maintaining production ML pipelines, including automated data ingestion, feature engineering, model training, validation, and deployment on major cloud platforms (AWS, Azure, GCP).
Developing, implementing, and optimizing complex machine learning models (including deep learning, NLP, and advanced Generative AI models like LLMs and RAG systems ) to solve specific client challenges.
Working closely and effectively with client software development and DevOps teams to ensure ML model artifacts and APIs are consumable, maintainable, and deployable within existing application stacks and CI/CD pipelines.
Architecting ML solutions for high availability, low latency, and massive scalability to meet enterprise-level traffic and data volume requirements.
Translating client business requirements and software constraints into ML system architecture design and engineering tasks.
Implementing best practices for Model Governance, including drift detection, bias mitigation, security protocols, and comprehensive model documentation for auditability and compliance.
Providing technical guidance and mentorship to Associate Engineers and contributing to the CoE s knowledge base regarding emerging ML technologies and best practices in an IT services context.

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