Machine Learning Specialist

162 years

0 Lacs

Posted:1 week ago| Platform: Linkedin logo

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Work Mode

On-site

Job Type

Full Time

Job Description

About Birlasoft:

Birlasoft, a powerhouse where domain expertise, enterprise solutions, and digital technologies converge to redefine business processes. We take pride in our consultative and design thinking approach, driving societal progress by enabling our customers to run businesses with unmatched efficiency and innovation. As part of the CKA Birla Group, a multibillion-dollar enterprise, we boast a 12,500+ professional team committed to upholding the Group's 162-year legacy. Our core values prioritize Diversity, Equity, and Inclusion (DEI) initiatives, along with Corporate Sustainable Responsibility (CSR) activities, demonstrating our dedication to building inclusive and sustainable communities. Join us in shaping a future where technology seamlessly aligns with purpose.


About the Job – This role takes GenAI and ML models from experiment to secure, monitored production, embedding features like smart assistants, RAG search, summarisation, and decision support into our applications


Job Title - GEN AI developer

Location: bengaluru

Educational Background: Bachelor’s degree in computer science, Information Technology, or related field.

Mode of Work- Hybrid

Experience Required - • Minimum 6 to 8 years



Key Responsibilities



This role takes GenAI and ML models from experiment to secure, monitored production, embedding features like smart assistants, RAG search, summarisation, and decision support into our applications. Responsibilities include building and operating end-to-end MLOps/LLMOps pipelines, containerising and serving models, managing retrieval pipelines, and enforcing SLOs for latency, throughput, and cost. The engineer will integrate GenAI features with web applications, support POCs exploring agentic workflows, and implement governance and safety controls. They will monitor for drift, hallucinations, and privacy risks, ensuring compliance with Responsible AI and regulatory standards. Expertise in working with productionisation of LLMs—including fine-tuning, prompt/policy optimisation, and orchestration—is essential, alongside strong skills in Kubernetes, observability, vector databases, and cloud platforms.

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