Senior AI/ML Developer

What We’re Looking For: Education: Bachelors/Masters in CS/AI or equivalent industry experience (5+ years in ML, 2+ in GenAI). Technical Mastery: - Languages: Python. - Frameworks: Expert-level PyTorch, TensorFlow Extended (TFX), ONNX Runtime.  - Cloud: Certified in Azure AI Engineer Expert and/or GCP Professional ML Engineer. GenAI Expertise: Shipped production GenAI systems (e.g., 10k+ QPS chatbots, code autocomplete at GitHub Copilot scale). Advanced prompt/response engineering: Self-critique chains, LLM cascades, guardrail-driven generation. Preferred Qualifications Additions: Certifications: - Azure: Microsoft Certified: Azure AI Engineer Associate.   - GCP: Google Cloud Professional Machine Learning Engineer. Experience with hybrid/multi-cloud GenAI deployments (e.g., training on GCP TPUs, serving via Azure endpoints). Job description We’re a software house passionate about building solutions that change how our clients use data and artificial intelligence. For over 9 years, we’ve been developing innovative AI-driven products such as InfraSenses and SolarSpy — not just using ready-made tools, but also building machine learning models from scratch. We’re looking for an experienced Senior AI/ML Developer (GenAI) to join our Client’s AI engineering team in the insurance industry, building enterprise-grade Generative AI and LLM solutions that are redefining intelligent insurance platforms. You’ll design, deploy, and optimize multi-cloud GenAI systems, leading innovation in LLM orchestration, multimodal architectures, and scalable AI pipelines. This is a hands-on technical leadership role, combining development with mentoring and ensuring solutions meet business, performance, and ethical AI standards. Work with cutting-edge technologies like Azure OpenAI, GCP Vertex AI, AWS Bedrock, PyTorch, and LangChain, and help shape the AI strategy and best practices for global-scale projects in the insurance domain. Must-Have Experience: Cloud AI experience: Azure: Designed solutions with Azure OpenAI, MLOps Pipelines, and Cognitive Search.   GCP: Scaled Vertex AI LLM Evaluation, Gemini Multimodal, and TPU v5 Pods. High-Impact Projects: Automation projects to reduce significant $$ costs.   Built RAG  systems with hybrid search (vector + lexical) and dynamic data hydration.  Led AI compliance for regulated industries (healthcare, finance). What We Offer: The opportunity to build advanced Generative AI and LLM solutions for a leading insurance industry client. Work with cutting-edge AI technologies (Azure OpenAI, GCP Vertex AI, AWS Bedrock, PyTorch, LangChain) on global-scale projects. Professional growth and mentorship from top-tier AI/ML experts in an international environment. A training budget to support your technical and professional development Private medical care and co-financing of a sports card Flexible working hours and the option to work fully remotely ,[Design and build multi-LLM systems (e.g., Mixture-of-Experts, model routing) to improve cost and performance., Develop efficient training pipelines for large models using GPU/TPU optimizations (FSDP, DeepSpeed)., Build GenAI platforms across multiple clouds (Azure, GCP, AWS) with unified MLOps., Implement enterprise-grade security: private endpoints, VPC peering, data residency compliance., Develop new GenAI use cases such as agent workflows, synthetic data generation, and real-time fine-tuning., Create AI governance processes: model cards, drift monitoring, red-teaming protocols., Work with leadership to define AI roadmaps and ROI metrics., Mentor junior engineers and promote GenAI best practices.] Requirements: Machine Learning, GenAI, AI, Python, Azure Additionally: Sport Subscription, Training budget, Private healthcare, International environment, Remote work, Flexible working hours.