Requirements

Expected technologies

Python

LLM

AZURE

Our requirements

• Proven experience delivering cloud-based AI solutions with Azure OpenAI and GCP Vertex AI (including MLOps pipelines and multimodal models).
• Strong hands-on background in LLM evaluation, optimization, and scaling on platforms like Gemini and TPU v5 Pods.
• Demonstrated success in automation projects that drove measurable cost reductions.
• Experience building RAG systems with hybrid (vector + lexical) search and dynamic data hydration.
• Solid understanding of AI compliance and governance, especially in regulated industries (healthcare, finance).
• Proficiency in Python, PyTorch, and TensorFlow, with expertise in large-scale model deployment.
• A strategic and collaborative mindset — combining technical leadership with business impact.

Optional

• Certifications in cloud-based AI:
• Microsoft Certified: Azure AI Engineer Associate
• Google Cloud Professional Machine Learning Engineer
• Experience with hybrid or multi-cloud GenAI deployments – e.g., training models on GCP TPUs and serving them via Azure endpoints.
• Familiarity with best practices for scalability, security, and cost optimization in cloud-based AI/ML environments.

Your responsibilities

• Lead end-to-end projects in Generative AI and Large Language Models (LLMs) — from research to production
• Architect multi-LLM systems (e.g., Mixture-of-Experts, LLM routing) for cost and performance optimization
• Design GPU/TPU-optimized training pipelines for billion-parameter models using FSDP and DeepSpeed
• Build multi-cloud GenAI platforms (Azure OpenAI, GCP Vertex AI, AWS Bedrock) with unified MLOps
• Ensure enterprise-grade security and data compliance (VPC peering, private endpoints, data residency)
• Develop and implement AI governance frameworks – model cards, drift monitoring, red-teaming
• Drive innovation through agentic workflows, synthetic data generation, and real-time fine-tuning
• Collaborate with leadership to define AI roadmaps and ROI metrics for business impact
• Mentor and guide data scientists and ML engineers, fostering technical excellence and innovation
• Qualifications: 8+ years in ML (2+ in GenAI), proficiency in Python, PyTorch, TensorFlow (TFX), and experience with Azure / GCP AI platforms