Work on building ground truth, defining and collecting training datasets, implementing training pipelines and real-time inference (PyTorch, TensorFlow, TensorRT, Python, C++) for NVIDIA's Autonomous Vehicles effort. Requires advanced experience in deep learning/machine learning and computer vision (PhD+4 years or MS+6 years experience stated), plus skills in sensor fusion (e.g., images and LIDAR), planning/control, software engineering and research. Salary ranges provided: 184,000–356,500 USD/year depending on level.

Full-time role based in Foster City, CA (in-office Mon/Wed/Fri). Responsible for measurement and analytics for Trust & Safety (abuse prevalence, fraud loss, false positives/negatives, time-to-detect/mitigate, appeals), building reliable datasets and dbt models, developing and evaluating risk and anomaly-detection models, designing offline evaluations and experiments, and partnering with Engineering, Support, Legal, and other teams to operationalize detections and reduce abuse while minimizing friction for legitimate users. Requires 5+ years experience, strong SQL and Python skills, and experience with large behavioral datasets and predictive models.

NVIDIA seeks a Senior System Software Engineer to lead and advance AI-Perf, the company's framework for benchmarking and analyzing LLMs and inference workloads. Role involves designing benchmarking methodology, building high-performance measurement features, integrating with NVIDIA inference stacks and open-source frameworks, and collaborating with researchers and platform teams. Requires 3+ years in systems software or AI infrastructure, expert Python, and deep distributed-systems knowledge. Posted for US candidates (remote options); salary range listed in posting: 152,000–287,500 USD/year.

Senior role responsible for designing, building, and operating enterprise-grade data systems and platform capabilities to support analytics and AI/GenAI products. Responsibilities include centralizing data collection/transformation/storage/serving, supporting ML/GenAI and reporting teams, operational management of data infrastructure and tooling, and establishing standards for security, privacy, and governance. Role is open across the US with hybrid expectations for hub-based employees and travel requirements (up to 25% for hub-based, up to 50% for remote). Salary ranges provided: $216,000–$270,000 (NYC/SF) and $194,400–$243,000 (other locations).

Work on designing, developing, optimizing, and deploying large language models and NLP systems for safety and rule enforcement. Implement and maintain distributed training pipelines, optimize hardware utilization, conduct model evaluations and bias mitigation, and collaborate with cross-functional Safety teams. Requires 5+ years of MLE experience, strong Python and deep learning framework skills (TensorFlow, PyTorch, Hugging Face), and experience with distributed training frameworks.

NVIDIA is hiring a Utilities and Energy Sector / Grid AI Solutions Architect to develop GPU-accelerated AI and simulation solutions for transmission, distribution, generation owners, and grid-software vendors. Role requires deep power-systems domain knowledge, Python and GPU experience (CUDA/RAPIDS), familiarity with power-system tools and standards, and over 4 years of relevant professional experience; up to 20% travel.

Lead design and implementation of agentic AI solutions that integrate enterprise data, using deep learning, reinforcement learning, inference optimization, and model fine-tuning. Collaborate with engineering teams, prototype with Python/C++, work with GPUs and frameworks like TensorFlow/PyTorch, and contribute feedback to improve NVIDIA AI Enterprise software.

Join NVIDIA's energy team as a Solutions Architect focusing on last-mile deployment of AI in control rooms, plants, substations, and field sites. Responsibilities include architecting GPU-accelerated solutions, building industrial digital twins with Omniverse, deploying edge AI (Jetson/IGX), improving OT cybersecurity (Morpheus, BlueField), and implementing predictive maintenance and forecasting. Requires demonstrated experience with OT/ICS (SCADA, DCS, EMS/ADMS/DERMS), power-system modeling tools, Python, deep-learning frameworks, containerization (Docker, Kubernetes), and a minimum of 4 years' relevant experience. Up to 20% travel.

Lead cross-functional teams to define platform architecture and APIs for agentic workflows, standardize and automate agent frameworks (e.g., LangChain, AutoGen), build GenAI SDKs/CLIs, implement trust & safety guardrails, optimize orchestration and cost, and own Kubernetes Helm charts/operators. Requires deep engineering and AI/ML experience (minimum 8 years with a Master’s or 10 years with a Bachelor’s), strong cloud and K8s expertise, and experience deploying responsible, scalable AI systems.

Lead role responsible for probabilistic identity resolution, measurement and experimentation (lift and attribution), defining signal strategy and evaluation frameworks, and driving cross-functional execution with engineering, product, and sales. Requires an advanced degree (M.S. or Ph.D.) with significant industry experience (M.S.: 10+ years; Ph.D.: 6+ years) and strong skills in statistical programming (Python or R), SQL, machine learning, experimental design, and causal inference. Remote — United States.

Senior Staff Data Scientist role on Reddit's Ads Data Science team to define technical vision and lead measurement, experimentation, attribution, identity, and privacy-aware modeling. Requires 10+ years of industry experience, advanced quantitative training (or equivalent), and strong skills in causal inference, experimentation, statistical modeling, SQL, and Python/R. The role is remote for U.S.-based candidates and focuses on building scalable, privacy-compliant measurement systems and cross-functional influence.

Capital One seeks a Distinguished Engineer to define architecture and build agentic AI systems for real-time personalized marketing and assistive sales tools. The role requires hands-on prototyping, cross-organizational collaboration, and leadership in enterprise architecture and large-scale system design. Minimums include a Bachelor's degree and at least 7 years of software engineering and enterprise architecture experience.

Veeva Systems seeks a Data Scientist to develop statistical and machine-learning methodologies on US healthcare claims and financial data, build entity-resolution and affiliation/network mapping models, and infer organizational structure from noisy data. Requires 5+ years of data science experience and 5+ years working with healthcare data; base pay range listed as $95,000–$140,000.

NVIDIA seeks a senior machine learning/graphics engineer to apply AI and deep learning research to productize neural graphics for gaming, AR, and pro-visualization. The role requires expertise in ML/DL, real-time computer graphics, CV, strong programming skills (Python, C++, CUDA), and experience with TensorFlow/PyTorch. Position is US-based (Durham and Santa Clara listed) with remote options; salary ranges provided for levels 5 and 6.

The Home Depot is hiring a Senior AI Engineer to design, build, and operate production-grade agentic AI systems (LLMs, SLMs, RAG, multi-agent workflows) and the supporting cloud-native infrastructure. Role emphasizes Python development, orchestration, MLOps/LLMOps, Kubernetes/Docker, Terraform, vector DBs, observability, and integration with enterprise systems. Position is remote (Colorado), requires 6+ years of relevant experience, and lists a salary range of $100,000–$180,000/year.

Responsible for end-to-end model training strategy and data management for Commercial AI products (LLMs and traditional ML). Tasks include fine-tuning LLMs (QLoRA/LoRA/PEFT), building reproducible training pipelines, data governance/versioning, experiment tracking, distributed training and GPU optimization. Requires 12+ years of relevant AI/ML engineering or data engineering experience. US remote role; US base salary range $159,600–$207,500/year.

Lead the design of orchestration and abstraction layers that connect LLMs to tools, data, and sub-agents; build and operate MCP (Model Context Protocol) servers; define tool-surface strategy and multi-agent patterns. Own retrieval/RAG design (chunking, embeddings, vector stores, hybrid search, re-ranking), context-window and memory strategies, routing, observability, evaluation, and security controls. Requires deep hands-on experience with orchestration frameworks and retrieval systems, strong platform/API design skills, and at least 12 years of software/AI engineering experience.

NVIDIA seeks a Senior AI/Deep Learning Compiler Engineer to analyze deep learning networks and develop compiler optimization algorithms and code-generation techniques. The role requires strong CUDA and GPU performance debugging skills, experience with compiler technologies (e.g., MLIR, LLVM, XLA, Triton), and proficiency in C/C++ and Python. The position lists a minimum of 3+ years' relevant experience and provides a base salary range of 152,000–241,500 USD per year.

Gremlin seeks a Data Scientist, AI/ML to analyze millions of chaos engineering experiments and build ML systems that detect, classify, explain, and remediate failures. Responsibilities include pretraining/fine-tuning models, developing scalable data pipelines and feature stores for training and real-time inference, and applying techniques such as causal inference, graph ML, time-series modeling, and reinforcement learning. The role requires 5+ years of professional experience building and productionizing machine learning systems; the position is remote and based in the US and does not offer visa sponsorship.

Remote Director of Applied AI Product reporting to the Chief Strategy Officer. Hands-on role building and shipping AI-driven product and agentic workflows against real client data, owning technical approach, roadmap, discovery, measurement of client outcomes, and operational rollout/enablement. Requires director-level product experience, AI fluency, SQL and data-warehouse familiarity, and track record of shipping production software that drives measurable business outcomes.