Lead development of NOC performance and functional models using AI technologies, define features for GPU memory and interconnect subsystems, analyze benchmarks and simulation/emulation results to identify optimizations, and collaborate with engineering teams. Requires Bachelor's or equivalent, 15+ years relevant experience, strong performance modeling and large-scale software development experience, proficiency in C/C++ and Python, and deep GPU architecture and memory/interconnect expertise.

NVIDIA is hiring a Senior Solutions Architect to lead customer technical engagements with hyperscalers and cloud providers for AI training, inference, and large-scale AI infrastructure. Requires 8+ years experience, strong Linux and ML infrastructure knowledge, and proficiency in Python; experience with GPUs/CUDA, containerization (Docker/Kubernetes), distributed training, and frameworks like PyTorch or JAX is desirable. Posted salary ranges from USD 184,000 to 356,500 per year across levels.

Join NVIDIA's DGX Cloud Lepton team to design, build, and maintain scalable AI infrastructure and tooling for large-scale training, inference, fine-tuning, and Agentic AI. Requires 8+ years building software infrastructure for large-scale AI systems, strong debugging and root-cause analysis skills, experience with distributed systems, Kubernetes, observability (e.g., ELK, Prometheus, Loki), and proficiency in Python and C/C++.

Lead technical authority in a Commercial AI Center of Excellence to design and evolve shared AI services, agentic frameworks, and paved-road patterns. Requires 15+ years in AI/ML software engineering, deep expertise in distributed/cloud-native systems, hands-on production LLM and RAG experience, and strong Azure/cloud platform knowledge; responsible for architecture, standards, performance/cost optimization, and cross-team technical influence in regulated SaaS environments.

Serve as the technical authority for AI quality and risk controls within the Commercial AI CoE: design and implement AI evaluation frameworks (gold datasets, regression testing, CI gates), lead model validation, telemetry, and drift detection, and partner with Legal, Security, and Risk to translate policy into technical controls. Requires 15+ years of AI/ML engineering experience.

Work on the open-source Triton compiler to design and implement compiler technology (using MLIR and Triton's Python DSL), optimize high-level kernels to efficient low-level GPU code, and hand-tune critical paths (inline PTX). Collaborate with hardware architects and the CUDA compiler team; experience tuning BLAS/deep-learning kernels, numerics/linear algebra, and ML compilers (TVM/MLIR) is a plus. Base salary range: 184,000 USD - 287,500 USD per year.

Customer-facing Staff Forward Deployed Engineer responsible for architecting, deploying, benchmarking, and optimizing production AI/agentic systems (inference, runtimes, orchestration) on DigitalOcean’s platform. Role includes building deployment frameworks and tooling, validating platform capabilities, collaborating with vendors and partners, and up to 30% travel for customer engagements.

NVIDIA is hiring a Solutions Architect to integrate GPU-accelerated software and tools with OEM partners, design multi-TB/PB accelerated pipelines, develop proofs-of-concept, and guide Agentic AI workflows (semantic search, RAG, GNN). Requires 5+ years of relevant experience and strong skills in Python, C/C++, Linux, Spark, ML/DL, and GPU acceleration. Salary ranges provided (USD 152,000–287,500/year).

Client-facing role responsible for architecting end-to-end, secure, scalable GenAI solutions on Gemini Enterprise, including multi-agent workflows, RAG-based data grounding, and security/governance. Requires 6+ years in solutions/cloud architecture or senior technical consulting with deep hands-on experience in Gemini, Google Workspace integrations, BigQuery, LLMs, prompt engineering, and Python.

GitLab seeks a Distinguished Engineer to pioneer autonomous, agentic SDLC capabilities: identify high-impact use cases across planning, coding, security, and operations; run hands-on experiments and benchmarks; design reference architectures, guardrails, and observability; mentor senior engineers; and convert internal patterns into product features while ensuring multi-tenant, compliance, and data-governance requirements are met. Requires 10+ years engineering experience and deep expertise in AI/ML, LLMs, distributed systems, and responsible AI.

Lead the identification, prioritization and delivery of AI-forward technologies for network partners and the global organization, including classroom data tools, learning platforms and constituent feedback systems. Manage a small team (two solutions engineers and a UI/UX specialist), build a community of technology enthusiasts across the network, gather requirements, define success metrics, and coordinate implementation with internal teams and external partners. Role is 100% remote, three-year fixed-term, requires valid local work authorization, and requests application materials in English.

Build and iterate on AI-powered product experiences (chat, remediations, codefixes) by developing backend systems, prompts, and evaluation loops to productionize LLM-driven workflows. Requires ~5+ years experience, strong backend engineering (Go or similar), hands-on experience with LLM-based systems and prompt engineering, and ability to collaborate with product and design. Kubernetes and operational remediation experience are a bonus.

NVIDIA seeks a Senior DL Algorithms Engineer to enable and optimize open LLM/Omni models (e.g., Nemotron, Cosmos) on NVIDIA's accelerated inference software stack. Responsibilities include contributing to open-source frameworks (TRT-LLM, vLLM, SGLang, FlashInfer), profiling and removing bottlenecks across the inference stack, benchmarking, and co-designing with partner teams. Requires 3+ years' experience, strong deep learning and inference background, GPU performance optimization, PyTorch or equivalent, and understanding of computer/GPU architecture.

Role focuses on research, implementation, and validation of model and algorithm improvements for human-centric video generation and world models. Responsibilities include prototyping spatial multimodal and neural-rendering approaches, improving training and inference efficiency, defining training objectives for sim-to-real/real-to-sim generalization, building domain-specific benchmarks, and translating research into production-grade checkpoints and integrations. Requires PhD or equivalent, 8+ years applied research/industry experience, 3+ years designing/training generative models, and advanced proficiency in Python, PyTorch, C++, and CUDA.

Embed with Distribution, Logistics, Purchasing, Member Care, and Supply Chain to identify and prioritize AI and automation opportunities. Audit workflows across SAP, Salesforce, and other enterprise systems, design and build AI-powered tools and automated workflows, and document measurable process improvements. Work directly with the COO and functional leaders and establish a scalable AI practice within Operations.

Lead technical vision and delivery of scalable ML models and language-based applications at Headspace, shape the internal ML platform, partner with cross-functional teams, and mentor engineers. Required: Master's degree or equivalent, 8+ years ML engineering experience, Python, experience with vector search, embeddings, recommender systems, supervised/unsupervised/deep/reinforcement learning, LLM orchestration/RAG, and modern ML/NLP libraries (scikit-learn, PyTorch, TensorFlow, spaCy). Preferred: PhD, clinical/healthcare ML experience, familiarity with current ML literature and scalable service implementation, and AWS experience (SageMaker, Lambda, S3, DynamoDB, IAM). Position is full-time, US-based (preferred locations: San Francisco hybrid; New York City and Seattle remote). Salary range listed: $162,000–$225,000 (USD, annual) with a higher location-based range for some cities.

Chainguard seeks a Senior Software Engineer to architect and implement an automation platform for package creation, test generation, and image building. The role focuses on Go development, LLM/agent integration, developer tooling, and supply chain security; the position is remote (Canada, United States, Europe) and lists a base salary range of $157,000–$184,000 USD per year.

Join GitHub's Copilot Agents organization to design, implement, and operate Blackbird—the platform's lexical and semantic code search engine. Responsibilities include building scalable, high-performance code search, integrating AI/ML features and agents, driving technical roadmap, participating in on-call rotations, and mentoring other engineers. Required experience ranges (minimum explicitly stated in posting is 3+ years in certain qualification paths); preferred experience includes web-scale search, systems programming (Rust), and AI/ML integration.

Contract Lead Instructor (2-week, ~30 hrs/week) delivering live remote instruction and hands-on labs on MLOps and AI platform engineering. Requires 7+ years in software/data engineering, 3+ years in MLOps/ML platform roles, deep Azure ML / AI Foundry experience, Python and ML CI/CD knowledge, and certifications AZ-900, AI-900, DP-100 (AI-102 preferred). Engagement is remote and must align with Pacific Time; estimated lump-sum compensation $11,500–$15,500 for the program.

Deliver synchronous remote lectures and hands-on labs focused on designing and building multi-agent systems using Azure AI Foundry, Copilot Studio, and Semantic Kernel. Requires 7+ years in software engineering, 2+ years building/deploying agentic AI systems, expert Python skills, API design, advanced prompt engineering, and AZ-900 and AI-900 certifications (AI-102 strongly preferred). Must be available ~30 hours/week during West Coast (Pacific Time) hours for the engagement.