Machine Learning Architect

• 8-10 years of experience: Must have worked as a data engineer before venturing into AI/ML/Generative AI development.
• Coding experience: Proficient in a core programming language (Python, Java, Scala, Spark) and willingness to be partly billable in client projects.
• In-depth understanding: Of cloud platforms and various services on AWS/GCP and Azure, ML Platforms such as SageMaker, Vertex AI, and the latest GenAI services stack.
• Knowledge of: Machine Learning, Deep Learning, Generative AI/LLMs, and various use cases.
• Proficiency with: Big Data Analytics technologies, including hands-on expertise in building complex AI/ML and Data proofs-of-concept on public cloud platforms.
• Familiarity with visualization tools: Such as Tableau.
• Experience in: Discovering use cases, scoping, and delivering complex solution architecture designs to diverse audiences, adapting technical depth as needed.
• Understanding of: DataOps, MLOps, LLMOps, Observability, DevOps, and SRE concepts.
• Understanding of: LLM Prompts Engineering, LLM Finetuning, Open source LLM, and the latest tech innovations.

Client-facing skills and relationships:

• Engage customers in technical sales, confidently answering questions, guiding outcomes, and communicating technical value propositions.
• Enthusiasm for working with clients across HiTech industries (Information Services, Healthcare, Life Sciences, eBusiness, etc.) and gaining deep knowledge in these verticals.
• Ability to build strong customer relationships and collaborate internally with sales, delivery, and practice teams.

*Hands-on presales experience: In the AI and Data services industry. The ideal candidate would have collaborated with large analytics, AI, and ML consulting services organizations.

Additional desirable skills:

• Experience building demos for Generative AI.
• Exceptional communication and storytelling abilities.