Lead and develop an 8-person engineering team responsible for roadmap and execution of anomaly and signal detection systems that combine distributed systems and ML/LLM. Work closely with product and applied scientists to build and evaluate production ML/LLM systems at scale; the role is based in New York with a hybrid workplace. Reasonably estimated salary range for this role is $192,000–$240,000 USD per year.

Work on design, training, optimization and productization of ML models for LiDAR/camera perception and multi-sensor fusion (detection, segmentation, tracking). Requires 8+ years industry experience, strong C++ and Python skills, deep learning framework experience (PyTorch/TensorFlow), and experience delivering ML into production for automotive or related robotics platforms.

Work on the Elasticsearch Inference API and plugin: design protocols, implement streaming (SSE) and async execution, handle schema negotiation, rate limiting, chunking and billing integration. Collaborate with the wider inference and Kibana teams, participate in on-call rotation, review OSS contributions, and write unit and integration tests. Requires 5+ years production Java experience.

Work on designing and training large-scale generative, imitation, and reinforcement learning models and building LLM/VLM/VLA systems for deployment in production autonomous vehicles and robotics. Responsibilities include dataset generation/collection, model pre-training and fine-tuning, integrating models with vehicle firmware for safety-critical systems, and collaborating with cross-functional teams to meet performance, safety, and reliability requirements. Required: strong ML and deep learning background, production deployment experience, Python and C++ proficiency; PhD+4 years or MS+6 years of relevant experience noted.

Lead a team of full-stack data scientists responsible for client acquisition, retention, and reactivation across paid media, onboarding, site experiences, CRM, incentives, and reactivation. Role emphasizes experiment design and interpretation, predictive modeling, personalization, production deployment, cross-functional partnership, and developing a focused data science strategy. Requires 5+ years applying ML/experimentation and 2+ years managing technical teams. US-based salary range $200,000–$245,000 USD.

Design, build, and operate agent-to-agent (A2A) architectures and multi-agent orchestration; integrate and optimize LLMs (including prompt engineering and tool calling); implement RAG and vector search grounding; provision scalable cloud infrastructure with IaC (Terraform) and DevOps practices; and apply security, observability, and governance for multi-agent workflows.

NVIDIA seeks a PhD intern to research, design, and implement methods for efficient deep learning across diffusion language models, multimodal generation, and hybrid cloud–edge agentic systems. The role requires pursuing a PhD, strong knowledge of machine learning and deep learning, experience with LLMs/diffusion/multimodal or agentic systems, hands-on large-scale model training including data preparation and model parallelization, and an outstanding research track record (at least one top-tier conference publication). Hourly intern rate is listed as 38 USD–94 USD; applications accepted until at least October 11, 2026.

Cribl seeks a staff-level engineer to build and operate production agentic systems and platform harnesses (orchestration, tool integrations, runtime, guardrails). The role focuses on intent engineering, agent orchestration, event-driven architectures, observability, CI/CD with progressive delivery, and driving adoption across engineering. Primary stack is TypeScript/Node.js; experience with LLMs, distributed systems, cloud operations, and security/permissions is expected.

Role to design and build AI-enabled tools, pipelines, and agentic workflows integrating AI models with DCC applications, APIs, and production infrastructure to support artists and engineers. Requires 8+ years of software engineering experience, strong Python skills, experience with content pipelines and DCC integrations, and 2+ years of technical leadership. Location listed in the US (Santa Clara) with remote option; employer: NVIDIA.

NVIDIA is hiring a Senior Solution Architect for the AI Factory to architect and scale high-performance distributed AI infrastructure (on-prem and cloud) using NVIDIA GPUs. The role involves technical customer engagement, integrating NVIDIA technology into HPC and deep learning architectures, supporting development and POCs/POVs, and showcasing the AI ecosystem. Requirements include a B.Sc/M.Sc (or equivalent), 5+ years in software development or ML engineering, practical on-prem Kubernetes experience, familiarity with containers and MLOps tools, and knowledge of PyTorch, vLLM, and TritonServer.

Lead data science work for Consumer and Developer Experience product strategy: collaborate with product, engineering, and analytics teams; develop and productionize machine learning models (design, training, evaluation, validation, implementation); analyze large numeric and textual datasets using tools such as Python, Conda, AWS, H2O, Spark, and relational databases. Remote-eligible; employer may sponsor employment authorization.

Lead engineering work across agents, automations and skills for the Context Engine: ship TypeScript/Python production code, design telemetry and evaluation strategies, iterate on prompts/skills/memory safely, and partner with data scientists and product to measure and improve agent behavior.

Join the Context Engine team to build the knowledge layer agents use with Elasticsearch. The role involves writing production TypeScript/Python code, designing telemetry and evaluation strategies, iterating on prompts, skills and automations safely in production, and partnering with data scientists, backend engineers and product. Requires 10+ years of software engineering experience and experience shipping AI-driven products on production traffic.

Build state-of-the-art generative pipelines and end-to-end image/video editing capabilities for ad creative, including LLM/VLM fine-tuning and RLHF/RLPF using ad performance signals (CTR/CVR). Lead implementation of safety, brand-preservation, and compliance systems while partnering with Product, Sales, Policy, UX, and Ads ML teams to integrate capabilities into the ad product.

NVIDIA seeks a Senior System Software Engineer to develop and optimize GPU-accelerated, containerized pipelines for indexing, deduplicating, filtering, and classifying multimodal datasets used in LLM and Agentic Retrieval systems. The role involves Rust and Python development, benchmarking/profiling, MLOps (Docker-Compose, Containers, Kubernetes), collaboration with LLM/ML researchers, and improving system speed, cost, and accuracy. Requires 6+ years' experience. Location: United States (multiple offices) and remote.

NVIDIA Developer Technology Engineer focused on GPU-accelerating generative AI (LLMs, diffusion, multimodal) and other ML workloads. Role involves performance analysis and low-level optimization, contributing to training/inference frameworks and libraries, working with external developers and internal research/engineering teams, and sharing results via blogs and conferences. Requires MS or equivalent and 1+ years relevant experience; programming fluency in C/C++ and knowledge of CPU/GPU architectures and parallel programming.

Senior IC responsible for technical vision, architecture, and roadmap for 3D obstacle perception (multi-camera and multi-sensor fusion) for autonomous driving. Will design and productionize efficient deep learning models, lead data and labeling strategy, define KPI frameworks, collaborate with safety and systems teams for deployment, and mentor engineers. Requires 15+ years experience, strong PyTorch proficiency, production experience with Python/C++, and familiarity with CUDA and GPU-accelerated pipelines.

Lead strategic partner engagements to architect, prototype, and scale enterprise-grade agentic AI systems including multi-agent workflows, RAG, tool use, guardrails, policy enforcement, and confidential deployments. Requires 8+ years experience, strong Python/Linux skills, hands-on work with LLMs/generative AI and frameworks (PyTorch/TensorFlow), and depth in AI/LLM security or confidential computing.

NVIDIA seeks a Senior Perception Engineer to develop and productionize the 3D obstacle perception stack for autonomous driving. Responsibilities include architecture and algorithm design, building transformer- and CNN-based 3D perception models using multi-camera and multi-sensor (camera, radar, lidar) fusion, BEV exploration, large-scale training (pretraining, distillation, LoRA), KPI definition, dataset analysis, and collaborating with data, safety, systems, and software teams to meet safety and deployment requirements. Qualifications specify PhD+4 years, MS+6 years, or BS+8 years of relevant experience and practical experience with PyTorch, Python/C++, CUDA, and taking models from prototype to production.

Role focuses on architecture, research, and productionization of radar-focused 3D obstacle perception and multi-sensor fusion (camera, radar, lidar) for L2–L4 autonomous driving. Requires 12+ years of experience in deep learning–based perception or radar signal processing, hands-on expertise with PyTorch, strong software engineering in Python/C++, and experience scaling models to production with GPU/CUDA optimizations.