Data Science Lead

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 are looking for an experienced Data Science Lead to design and deploy enterprise-grade Generative AI systems for our client in the insurance industry. The ideal candidate will drive innovation in LLM orchestration, multimodal AI architectures, and scalable AI/ML pipelines, owning the full lifecycle from research to production. This is a hands-on technical leadership role, combining individual contribution with mentoring and guiding junior developers.

Key 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

What We’re Looking For:

• 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.

Preferred Qualifications Additions:

• 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.

What We Offer

• The opportunity to lead cutting-edge Generative AI and Data Science projects for a leading client in the insurance industry.

• A chance to shape AI strategy and architecture in enterprise-scale environments.

• Collaboration with a team of experienced AI/ML and cloud engineering experts, fostering knowledge sharing and innovation.

• 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