Posted:1 week ago|
Platform:
On-site
Full Time
∙Lead the design, development, and deployment of Generative AI models and solutions on cloudÂ
platforms such as Microsoft Azure, AWS, or GCP.Â
∙Collaborate with cross-functional teams to understand business requirements and translate themÂ
into technical solutions.Â
∙Drive the end-to-end lifecycle of AI/ML projects, from data collection and preprocessing toÂ
model training, evaluation, and deployment.Â
∙Mentor and guide junior team members, fostering a culture of continuous learning andÂ
innovation.Â
∙Stay updated with the latest advancements in Generative AI and AI/ML technologies, andÂ
integrate them into ongoing projects.Â
∙Optimize and fine-tune AI models for performance, scalability, and reliability.Â
∙Develop and maintain comprehensive documentation for all AI/ML projects and processes.Â
∙10-13 years overall IT experience. Out of which 3-4 years hands-on experience in AI/ML, and atÂ
least 1 year in Generative AI.Â
∙Strong proficiency in Python programming and experience with AI/ML frameworks, models andÂ
algorithms. Â
∙Strong experience with leading LLMs, RAG, agentic automation, and agent frameworks likeÂ
Lang Chain, Lang Graph, AutoGen, AutoGPT for Generative AI use-cases.Â
∙Hands-on experience in Gen AI observability & monitoring via tools like Lang SmithÂ
∙Experience with deep learning, CNN, NLP, text-to-speech, speech-to-text, OCR, and imageÂ
processing techniques.Â
∙Experience in Infrastructure related use-cases leveraging Autonomous Agents and/or agenticÂ
platform. Should have hands-on experience building Autonomous agents for Gen AI related use-
cases.Â
Â
∙Extensive experience with cloud platforms (Microsoft Azure/AWS/GCP/IBM WatsonX) and theirÂ
AI/MLÂ services.Â
∙Extensive experience in Prompt Engineering and ability to design and build Prompt libraries forÂ
various scenarios applicable in Infrastructure.Â
∙Thorough understanding of Responsible AI best practices and standards and experience ofÂ
implementing them in Gen AI related projectsÂ
∙Proven track record of leading and delivering complex AI/ML projects.Â
∙Excellent problem-solving skills and the ability to work in a fast-paced, collaborativeÂ
environment.Â
∙Strong communication and leadership skills, with the ability to articulate technical concepts toÂ
non-technical stakeholders.Â
∙Experience with natural language processing (NLP) and computer vision.Â
∙Familiarity with MLOps practices and tools.Â
∙Knowledge of data engineering and big data technologies.Â
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