Lead Data Scientist (Nvidia)

Location: Mexico, Colombia, or Chile; remote/office work options

Company

hirify.global delivers engineering and technology consulting services, including enterprise AI solutions for global clients.

What you will do

• Lead end-to-end AI engagements from discovery and solution strategy through architecture, implementation planning, and production delivery.
• Translate business challenges into AI use cases, roadmaps, and scalable enterprise architectures.
• Design and validate production-ready Generative AI and Agentic AI solutions using NVIDIA technologies across cloud and on-premises environments.
• Define GPU infrastructure, Kubernetes orchestration, inference optimization, and reference architectures.
• Evaluate GPU utilization, latency, throughput, scalability, infrastructure efficiency, and LLM serving configurations.
• Lead technical discovery, workshops, proposals, proof-of-concept initiatives, thought leadership, and client collaboration.

Requirements

• 6+ years of experience in AI consulting, Generative AI, Agentic AI, Machine Learning, or Deep Learning, including client-facing engagements.
• Advanced expertise in Generative AI, Agentic AI, multimodal AI, transformers, LLMs, and VLMs.
• Hands-on experience with Python, PyTorch, TensorFlow, Hugging Face, Pandas, and NumPy.
• Experience with at least three NVIDIA AI technologies, such as NeMo, NIM, Triton, TensorRT-LLM, Riva, DeepStream, Metropolis, or Omniverse.
• Practical experience deploying AI workloads on Kubernetes with Helm, NVIDIA GPU Operator, GPU device plugins, MIG/vGPU partitioning, vLLM, or Ollama.
• Knowledge of inference optimization, GPU profiling, cloud AI deployments, enterprise architecture, distributed systems, MLOps, governance, stakeholder management, and English-language technical discussions.

Nice to have

• Bachelor’s or Master’s degree in Computer Science, Applied Mathematics, Physics, Engineering, or a related technical field.

Culture & Benefits

• Collaboration with NVIDIA stakeholders and multidisciplinary engineering teams.
• Opportunities to develop reusable accelerators, solution blueprints, and industry offerings.
• Remote or office work options in the specified locations.
• Opportunities for technical content creation, conference presentations, and mentorship.