Team Lead, Forward Deployed AI Engineering

About Rhino Federated Computing Rhino Federated Computing Rhino solves one of the biggest challenges in AI: seamlessly connecting siloed data, apps, and models through federated computing. Our platform enables our customers to share business insight and processing without compromising intellectual property, data privacy, or data security. Our Rhino Federated Computing Platform offers flexible architecture across multi-cloud and on-prem hardware, end-to-end data management controls and workflows, and privacy enhancing technologies. Rhino is trusted by over 60 leading consortia and enterprises worldwide, including 14 of 20 of Newsweek’s ‘Best Smart Hospitals’ and top 20 global biopharma companies. The company is headquartered in Boston, with an R&D center in Tel Aviv. About the Role As the Team Lead for the Forward Deployed AI Engineering Team, you will serve as a hands-on Player/Coach, leading a customer-facing AI engineering and scientist group responsible for deploying and scaling Rhino’s Federated Computing Platform (FCP) in complex, real-world environments. You will maintain a direct, hands-on contribution by working with customers’ technical and research teams to design, implement, and optimize federated AI models and systems. Critically, you will also coach, mentor, and manage a team of applied AI engineers, guiding them through federated model training, inference, deployment, and monitoring, while helping customers unlock the full potential of federated data collaboration. Your leadership will shape how federated AI is operationalized at scale. Key Responsibilities Technical Leadership & Delivery Lead the design and delivery of federated AI solutions across imaging, text, and structured data domains. Design and implement federated training and inference pipelines, integrating data preprocessing, model orchestration, and AIOps tooling. Own project execution from scoping to deployment — ensuring clarity, speed, and technical excellence. Customer Engagement & Enablement Partner directly with customers to understand workflows, map data ecosystems, and design scalable AI solutions. Serve as a trusted technical advisor on privacy-preserving ML, model optimization, and deployment best practices. Build long-term relationships that drive adoption and measurable outcomes for customer programs. Team Leadership Manage multiple concurrent engagements, balancing strategic leadership with hands-on problem-solving. Provide mentorship to Forward Deployed Engineers and Scientists, fostering a high-performance, learning-driven culture. Product Feedback & Innovation Identify reusable solution patterns and contribute to the standardization of federated AI workflows. Surface customer insights and field feedback that shape Rhino’s roadmap. Collaborate with product and research teams to prototype and validate new federated learning research and frameworks. Required Skills Experience: 5+ years in applied AI, machine learning engineering, or MLOps roles; experience deploying models in production environments. Technical Expertise: Deep hands-on experience with deep learning frameworks (PyTorch, TensorFlow, JAX) and AI/MLOps ecosystems. Generative AI Tools: Familiarity with LLM frameworks (GPT, Gemini, Claude, LangChain, agentic frameworks, etc.). Programming & Systems: Strong proficiency in Python, REST APIs, and data systems (SQL/NoSQL); comfort with cloud computing and GPU-based systems. Delivery Focus: Proven ability to own technical outcomes end-to-end, from scoping and prototyping to full-scale delivery. Collaboration: Excellent communication skills and the ability to operate across customer, product, and engineering teams. Mindset: Action-oriented, adaptable, and able to prioritize effectively in fast-changing environments. Preferred Skills Industry experience in healthcare, biopharma, financial services, and public sector. Ph.D. or M.S. in a quantitative field (Computer Science, Engineering, Biomedical Informatics, Bioinformatics, Chemistry, or related). Prior experience deploying federated learning, privacy-preserving AI, or secure distributed computing systems. Location Boston preferred, but open to other locations for highly qualified candidates. Visa Sponsorship We will sponsor visas for USA PhD candidates in the relevant areas - Mathematics, Artificial Intelligence, Federated Learning, Computational Chemistry/Biology/Biomedical candidates. An B.S./M.S. with extensive, directly relevant industry experience will also be considered.

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