Ai Ml Engineer

About the company:

ARAs client TechGlobal (pseudonym) is a global leader in strategy, technology consulting and digital services, enabling clients in more than 100+ countries to implement cutting edge solutions in their transformation journey. TechGlobal helps businesses become digital-first and digital-ready. The company has a global presence with 600000+ employees ( 200000+ in India). India is a focus for them with their Development Centres presence in over 10 locations across Tier 1 and Tier 2 cities. They are recognised for their people first and employee oriented policies. Along with offering hybrid work options, a Pan India presence gives flexible location options to employees.

About the role:

As an AI / ML Engineer, you will be responsible for developing applications and systems that utilize AI tools, cloud-based AI services, and on-premise or cloud-native application pipelines. The ideal candidate will have a strong foundation in deploying production-ready AI solutions and integrating Generative AI (GenAI) models into business applications.

Key Responsibilities:

• Serve as a Subject Matter Expert (SME) in AI/ML technologies.
• Lead, mentor, and collaborate with team members to ensure successful project delivery.
• Make key technical and strategic decisions across multiple teams.
• Design, build, and deploy scalable AI/ML solutions in production environments.
• Integrate large language models (LLMs) and generative AI solutions into enterprise systems.
• Engage in regular cross-functional collaboration to align AI/ML solutions with business goals.
• Conduct training sessions and facilitate knowledge sharing within the team.
• Ensure timely project execution in alignment with organizational strategy.

Must-Have Skills:

• Expertise in Large Language Models (LLMs) and their practical applications.
• Deep knowledge of deep learning frameworks such as TensorFlow and PyTorch.
• Proven experience deploying AI models on cloud platforms such as AWS, Azure, or Google Cloud.
• Strong grasp of natural language processing (NLP) techniques and tools.
• Ability to develop production-grade, scalable AI solutions.

Good-to-Have Skills:

• Experience with tools like Hugging Face Transformers or LangChain.
• Exposure to MLOps pipelines and containerization (Docker/Kubernetes).
• Familiarity with RESTful APIs, version control (Git), and CI/CD pipelines.

Experience and Qualifications

• Candidates must have a minimum of 7.5 years of experience in AI/ML roles, with a strong focus on Large Language Models.
• A 15-year full-time education background is mandatory