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Specialized senior ML/GenAI role with niche requirements, moderate applicant competition.
High because ML/GenAI production and cloud deployment skills are industry-specific and non-transferable.
Multiple explicit years and mandated ML/cloud/LLM production skills create strict shortlisting.
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Design, develop, and productionalize ML/GenAI applications including model evaluation, training, fine-tuning, and prompt engineering for LLMs.
Lead end-to-end design and architecture of scalable, reliable, cost-effective Generative AI solutions including RAG pipelines and agentic workflows.
Collaborate with cross-functional teams and lead ML/data science team (4+ members) to deliver projects from conception to deployment, ensuring quality and scalability.
Minimum 5 years experience designing and deploying ML/AI applications; 8 years in software engineering for secure, scalable, performant applications.
At least 2 years experience leading and mentoring ML/data science teams with 4+ members.
Proficiency with Python and ML libraries (e.g., TensorFlow, PyTorch, XGBoost, Scikit-learn, LangChain) and experience with cloud platforms like GCP or equivalent.
Experience with Document extraction AI, Conversational AI, Vision AI, NLP or Generative AI; Work Experience Required: explicit (5+ years ML/AI, 8+ years software engineering).
Experienced in building end-to-end scalable ML pipelines on cloud platforms, especially GCP or similar environments.
Strong in designing and deploying production-grade Generative AI models including RAG, fine-tuning, and prompt engineering for LLMs.
Capable leader of mid-sized ML/DS teams, comfortable owning full project lifecycle from design to deployment in AI/ML domains involving NLP, Vision, or GenAI.