דרושים Applied Ai Researcher - Digital Characters Avatars ב-אנבידיה ב-גרמניה

What you will be doing:

• Guide customers through the end-to-end process of AI adoption—from requirements gathering and proof-of-concept development to deployment, integration, benchmarking and ongoing optimization
• Collaborate with our business/account team to identify technical needs, customer goals, and strategies. Your responsibilities will include enabling customer adoption of NVIDIA technology by mapping our solutions to their use cases and driving positive relationships with our technology partners, making NVIDIA an integral part of end-user solutions.
• Keep up to date on AI advancements in Digital Biology as well as relevant NVIDIA technology that enable this innovation.
• Be a technical leader, bringing vision to the integration of NVIDIA technology into AI and HPC architectures for advanced applications, such as agentic AI, autonomous labs or drug discovery.
• Engaging with developers, researchers, data scientists, IT managers, and senior leaders internally and externally is an essential part of the Solutions Architect role to gain experience in various technical areas.
• Document what you know and teach others. This can vary from building targeted training for partners and other Solutions Architects to writing whitepapers, blogs, and wiki articles to simply working through hard problems with a customer on a whiteboard.
• We make heavy use of conferencing tools, but some travel is required for this role. You are empowered to find the best way to get your job done and make our customers successful.
  

What we need to see:

• MS or PhD (or equivalent experience) in Computer Science, Computational Biology, Computational Chemistry or Computational Physics, or related fields with strong applied experience in these domains.
• 5+ years of work-related experience with hands-on expertise in AI/ML for healthcare or life sciences.
• Proven experience with Python and AI/ML frameworks (PyTorch, Langchain, or building custom framework) and application to scientific questions.
• Strong time-management and organizational skills for coordinating multiple initiatives, priorities, and implementations of new technology and products into very complex projects.
• Motivated self-starter with an equal balance of strong problem-solving skills and customer-facing communication skills - especially in effectively presenting complex technical information. Must enjoy engaging with innovative individuals, continuous learning, and staying at the forefront of the field.
  

Ways to stand out from the crowd:

• Demonstrated work in AI-at-scale related to multi-omics foundation models, protein structure prediction, drug discovery or clinical development.
• Experience building, deploying, and optimizing agentic AI systems for healthcare and life sciences, especially for scientific software vendors and data platforms, is a plus.
• Experience developing, training and customizing Transformer models for healthcare and life sciences applications, especially using libraries like Transformer Engine or Megatron-LM.
• Background with accelerating scientific algorithms using parallel programming (e.g., using CUDA), or experience with distributed programming models for supercomputing applications, AI deployment/inference technologies (e.g. TensorRT), cloud deployment (AWS, Azure) or optimization frameworks (e.g. cuOpt), is a plus.
• Experience in the pharmaceutical industry or stablished thought leadership through publications or presentations on AI/ML applications in healthcare and life science.
  

What you'll be doing:

• Develop an MCP tool to analyse microservices logs.

• Build and extend log-analysis capabilities for large-scale microservice deployments.

• Create an AI Agent to orchestrate troubleshooting across multiple microservices.

• Integrate the MCP log-analysis tool into an autonomous agent.

• Automate triage, root cause analysis, and cross-service incident workflows.

• Implement observability and feedback loops for safe operation in production.

• Evaluate and compare ReFRAG, R2R, and other retrieval/agent methods.

• Design experiments to measure performance, cost, and reliability of competing approaches.

• Propose new architectures and approaches.

What we need to see:

• Currently pursuing a Bachelor's or Master's degree in Computer Science, Engineering, AI, Data Science, or related field.

• Strong programming fundamentals in at least one of: Python (preferred for AI frameworks), or Go.

• Solid understanding of data structures, algorithms, and API design.

• Basic knowledge of machine learning concepts, especially retrieval-based or agent-based architectures.

• Familiarity with Git, databases (SQL/NoSQL/Vector) and data pipelines.

• Strong problem-solving skills and eagerness to learn new technologies.

• Excellent communication and ability to work effectively in a team environment.

Ways to stand out from the crowd:

• Experience with RAG pipelines, vector databases, embeddings, or LLM orchestration.

• Exposure to MCP tools or multi-tool agent frameworks (Lang* stack preferably).

• Knowledge of containerization (Docker) and orchestration (Kubernetes).

• Familiarity with infrastructure automation.

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This role leads engagement with HCLS startups in the region and the broader startup developer ecosystem to accelerate the adoption of NVIDIA technology through scalable programming, hands-on engagement, and strategic partnerships. You will design, execute, and support programs to engage HCLS AI developers at scale —raising awareness, enabling trial and evaluation, surfacing feedback, and ultimately enabling HCLS startups to adopt NVIDIA technologies. You’ll identify where developers convene—innovation clusters, accelerators, regionally funded initiatives—and deliver creative, resonant programming across the region.

The ideal candidate brings 12 years+ of experience, can navigate fast-moving startup ecosystems, understands how to engage the HCLS startup community in the DACH region, including VCs and accelerators, and brings the creativity and intensity to lead teams, engage founders, and scale developer impact across the region.

What you’ll be doing

• Engage the HCLS AI Startup Community in the DACH region - Build and scale programs that connect regional HCLS startups to NVIDIA technologies, building from NVIDIA’s Inception programs, regional hubs, accelerators, and events efficiently at scale.

• Engage regional Venture Capital firms and funding entities at scale - Extend NVIDIA programs to regional VCs and other HCLS AI investors, engaging them to scale and accelerate adoption of NVIDIA technology to startups.

• Drive Regional Strategy, Execution, and Operational Excellence - Develop and execute regional strategies; define and track operational metrics to continuously improve startup and VC engagement at scale.

• Act as Regional Interface and SME - Serve as NVIDIA’s subject matter expert and main interface for the HCLS startup ecosystem in the DACH region, surfacing feedback and ensuring alignment with global teams.

What we need to see

• 12 years+ of experience in developing and delivering startup engagement programs at scale, developer relations, business development, or startup ecosystems

• BS or MS in engineering, biology, chemistry or equivalent experience

• Deep understanding of HCLS startup and VC communities in the region

• Track record of building and scaling developer or startup engagement programs

• Strong communication and program management skills

Ways to stand out from the crowd

• Knowledge of AI, machine learning, or HPC technologies

• Experience with regional VC, incubator hub, etc

• Familiarity with DACH region’s major startup hubs

NVIDIA is at the forefront of AI and accelerated computing, widely regarded as one of the most innovative companies in technology. You will have the opportunity to:

• Work with cutting-edge technology shaping the future of AI and startups

• Build communities and programs that empower thousands of developers

• Collaborate in a culture that values creativity, autonomy, and impact

What you’ll be doing:

• Conduct face-to-face and remote training sessions for NVIDIA’s customers and partners, with a willingness to travel up to 75% is required.

• Support developing training materials based on NVIDIA's innovative AI and data centre technologies.

• Collaborate with internal and external subject matter experts (SMEs) to support drafting course proposals aligned with market trends and customers' requirements.

• Work and train internal and external team members to deliver specific sessions of workshops.

• Build engaging lab-based training, incorporating diagrams, explanatory videos, and interactive hands-on exercises for the EMEA Channel landscape.

• Collaborate with SMEs to integrate key features of NVIDIA solutions into project-based learning experiences.

• Support developing instructor delivery notes, certification criteria, and assessment materials.

• Support with interpersonal aspects of training and workshop delivery.

What we need to see:

• Proficiency in delivering training and presentations, with the ability to effectively communicate technical concepts to partner audiences.

• Demonstrated ability to craft and implement accelerated computing solutions. Familiarity with tools such as SLURM, Kubernetes, Docker containers, Git, Python, CUDA, RAPIDS, and cloud service providers (AWS, Azure, GCP) is critical.

• A bachelor's degree or equivalent experience in computer science, mathematics, engineering, or a related field.

• Minimum 5+ years of technical field experience, with at least 5 years in data center-related technologies supporting AI such as storage, networking, or accelerated computing. Training delivery experience is required.

• Strong communication, interpersonal, and writing skills in English.

• Ability to work multi-functionally across different levels of a matrixed organization.

Ways to stand out from the crowd:

• Experience in delivering and developing in-depth training for technical selling audiences.

• Multi language preferred. English first language plus one additional. Preferable German or French.

• Proven experience in Field Engineering or Solutions Architect roles.

• Experience in optimizing workloads with GPU, like CUDA, CuDNN and TensorRT.

• A master's degree in computer science, mathematics, engineering, or equivalent experience.

What you'll be doing:

• Work closely with internal engineering and product teams and external app developers on solving local end-to-end AI GPU deployment challenges on the NVIDIA RTX AI platform.

• Apply powerful profiling and debugging tools for analyzing most demanding GPU-accelerated end-to-end AI applications to detect insufficient GPU utilization resulting in suboptimal runtime performance.

• Conduct hands-on trainings, develop sample code and host presentations to give good guidance on efficient end-to-end AI deployment targeting optimal runtime performance on NVIDIA ARM-based SoCs.

• Contribute code to internal and external projects, including open source.

• Collaborate with GPU driver and architecture teams as well as NVIDIA research to influence next generation GPU features by providing real-world workflows and giving feedback on partner and customer needs.

What we need to see:

• 5+ years of professional experience in local GPU deployment, profiling and optimization.

• BS or MS degree in Computer Science, Engineering, or related degree.

• Strong proficiency in C/C++, software design, programming techniques.

• Familiarity with and development experience on the Windows operating system.

• Experience with CUDA and NVIDIA's Nsight GPU profiling and debugging suite.

• Strong verbal and written communication skills in English and organization skills, with a logical approach to problem solving, time management, and task prioritization skills.

• Excellent interpersonal skills.

Ways to stand out from the crowd:

• Experience with GPU-accelerated AI inference driven by NVIDIA APIs, specifically cuDNN, CUTLASS, TensorRT.

• Detailed knowledge of the latest generation GPU architectures.

• Confirmed expert knowledge in Vulkan and / or DX12.

• Experience with AI deployment on NPUs and ARM architectures.

• Contributions to open source projects.