Technical lead responsible for architecting, building, and operating Kubernetes-native distributed inference hosting (prefill/decode disaggregation, KV-cache-aware routing, tiered caching, MoE support). Requires experience with LLM inference frameworks (vLLM, llm-d, Ray Serve, NVIDIA Dynamo), Go or Python, gRPC, observability and SLOs, performance optimization, and contributing to open-source inference projects.

Calendly seeks a Senior Full Stack Engineer to build production-grade React and TypeScript user interfaces and design backend APIs and services (Node.js, Ruby on Rails or similar) working with PostgreSQL and microservices. Requires 7+ years experience, participation in on-call rotation, experience in 0-to-1 product environments, and authorization to work in the United States. Salary ranges (annual, USD) provided.

Apiphani is hiring a Senior Software Engineer to design and implement backend services and orchestration layers (Python, TypeScript) that integrate LLMs, vector databases, and agentic workflows for a production AI automation platform. Requires 6+ years backend experience, strong AWS knowledge (including Bedrock), familiarity with RAG and vector DBs, and hands-on CI/CD and observability experience. Listed base salary: $120,000—$160,000 USD per year.

Join NVIDIA to design and implement robust map-based localization solutions for autonomous driving, working with large real and synthetic datasets. The role requires strong C++ and CUDA skills, experience in computer vision/3D geometry, and familiarity with automotive quality and safety standards such as ISO26262 and MISRA.

Work on designing and optimizing kernels, extensible abstractions for LLM serving engines, JIT domain-specific compilers, and inference runtimes for NVIDIA hardware. Qualifications include a Master's (PhD preferred) or equivalent experience, 6+ years in ML/DL systems development, experience with frameworks such as PyTorch/JAX/TensorFlow/ONNX, and expertise in GPU kernel development and compilers. Base salary range listed as 184,000 USD - 287,500 USD per year.

Join NVIDIA to develop AI inference systems, including kernel implementations, code generators, and runtimes to accelerate LLMs and other AI workloads. Requires a Master's (or equivalent) preferred PhD, 6+ years of ML/DL systems development experience, and strong experience with Python, C/C++, CUDA, deep learning frameworks, and GPU kernel performance optimization. Base salary range: 184,000 USD - 287,500 USD.

Lead technical strategy and deep engagements for AI Factory networking at strategic customers, acting as principal-level authority for products such as BlueField and ConnectX and technologies including DOCA, RDMA, RoCE, and InfiniBand. Requires 15+ years of industry experience, strong low-level software skills in C/C++, system-level debugging, high-performance networking, and expertise in performance tuning, reliability, and production hardening.

Lead design and delivery of scalable ML solutions (Generative AI, RAG, Graph ML, LLM fine-tuning) and high-performance real-time inference services. Hands-on responsibilities include architecture, microservices, Triton/TensorRT-based inference, Python development, CI/CD, Docker/Kubernetes, cloud deployments, and mentoring engineering teams.

Responsible for designing, building, and operating AI-based features (including LLMs, agent-driven experiences, RAG, and prompt engineering) across frontend and backend stacks. Requires 5+ years of software engineering experience, strong TypeScript/JavaScript and backend skills (Node.js/Go/Java), experience shipping AI/ML integrations in production, and familiarity with observability and telemetry systems.

Work on analyzing deep learning networks and implementing compiler optimization algorithms for AI inference across NVIDIA GPUs. Collaborate with deep learning framework and GPU architecture teams; require 3+ years relevant experience, strong C/C++ and Python skills, and experience with compiler technologies (e.g., MLIR, LLVM, XLA, Triton).

Join NVIDIA's Architecture Modeling group to model GPU architectures and baseboard components, develop and validate functional and performance simulation models, and build testing infrastructure. Requires 5+ years' experience, strong C/C++ and scripting skills (Python/Perl), familiarity with SystemC/TLM, and experience with ML frameworks such as PyTorch and TensorFlow.

Role responsible for improving ML training and inference efficiency across GPU clusters by debugging and optimizing software and infrastructure, building tools and frameworks to detect bottlenecks, collaborating with researchers across domains (LLMs, robotics, autonomous vehicles, video), and working with technologies such as CUDA, NCCL, Nsight, distributed training, cloud platforms, and fast distributed storage.

Work on implementing and optimizing language and multimodal model inference in NVIDIA Inference Microservices and TRT-LLM. Requires 5+ years experience, strong deep learning and inference background, performance profiling/optimization (especially GPU), and proficiency in C++ and PyTorch.

NVIDIA seeks a Senior AI Developer Technology Engineer to research and develop GPU-acceleration and optimization techniques for AI and financial-market workloads. Responsibilities include in-depth analysis and optimization on CPU/GPU architectures, collaborating with industry and academia, and publishing findings. Requirements: advanced degree or equivalent experience, 5+ years relevant experience, strong C/C++ programming, deep understanding of algorithms and linear algebra, hands-on low-level parallel programming (CUDA, OpenACC, OpenMP, MPI, pthreads, TBB), and CPU/GPU architecture knowledge. Base salary ranges provided (USD).

Udacity (an Accenture company) seeks an independent-contractor AI Mentor to guide managers and executives through business-focused AI coursework and projects. The role requires 5+ years in AI/ML/Data Science or AI product roles, direct production deployment experience, familiarity with generative AI (LLMs, RAG), agentic systems, model evaluation, and working with business stakeholders. Mentors provide practical, applied guidance, facilitate group sessions, and adapt explanations to varied technical fluency.

Join Invicti's AI team to design and build agentic AppSec solutions, including multi-agent systems, RAG and memory pipelines, MCP integrations, and prompt engineering. Requires 5+ years of production software development, strong Python skills, experience with LLM-powered apps/RAG/agentic AI, and knowledge of distributed systems, API design, and cloud-native architectures. Role involves cross-team collaboration, productization, and ownership from design to production.

Work as a senior fullstack engineer on Arize's AI observability platform, writing maintainable, scalable code primarily in TypeScript and React with opportunities in Python and Go. Responsibilities include API and domain model design, building reusable React components, researching and implementing visualization and dimensionality reduction algorithms in distributed environments, collaborating with product/design/customers, and contributing to architecture, code reviews, and documentation. Requires 5+ years frontend experience. Salary range listed: $125,000–$225,000/year.

Role on the Backend Engineering team to design, build, and maintain scalable analytics and backend services for an ML/LLM observability platform. Responsibilities include developing APIs, working with OLAP and distributed systems, integrating collection and monitoring tools, and contributing to open-source components. Requires 5+ years of backend experience and strong proficiency in languages such as Go, Python, Java, or TypeScript.

DataCamp seeks a Principal AI Engineer to develop the core AI tutoring system that provides real-time, adaptive learning. Responsibilities include prompt architecture and agentic workflow design, rigorous experimentation and custom evaluation metrics, integrating AI with platform and content pipelines, productionizing model interactions, and ensuring quality, safety, and observability. Requires 1+ years building LLM-based systems, strong Python and software engineering fundamentals, and experience with cloud/production infrastructure and CI/CD.

Design and evaluate GPU and system architectures to improve AI inference performance and efficiency. Build power and performance models of the AI inference stack, implement and test deep learning algorithms, and collaborate across software, research, and product teams. Requires MS or PhD (or equivalent), 5+ years relevant experience, strong math foundation in ML/DL, expert programming in C/C++/Python, and familiarity with GPU computing (CUDA) and HPC (MPI/OpenMP).