Role to lead architecture, quality, and adoption of an evaluation flywheel for NVIDIA's autonomous vehicle stack. Responsibilities include dataset curation and versioning, metric design and measurement (precision/recall), building self-serve dataset and metric pipelines, and partnering with engineering and AI model teams. Requirements include BS/MS (or equivalent), 12+ years building software with significant experience in autonomous vehicles, robotics, or large-scale ML systems, and strong Python and data engineering skills. Salary range provided: 224,000–356,500 USD/year.

Work on Dynamo's open-source GPU-accelerated inference stack, extending disaggregated serving across vLLM, SGLang, and TensorRT-LLM to support agentic inference (long-horizon reasoning, tool calling, stateful multi-turn execution). Responsibilities include inference-state management (KV/prefix caches, memory/storage hierarchies), building distributed frontends, optimizing throughput and latency, and contributing to upstream API compatibility. Requires 10+ years' experience, strong Rust and Python skills, and expertise in LLM inference and GPU optimization.

Work as the second builder on an AI-native growth engine to implement agent orchestrations, integrations with execution and analytics platforms, monitoring/audit logging, and content generation pipelines. Requires 3+ years building automation workflows or agentic systems, experience with LLM APIs, prompt engineering, and strong API integration skills; growth/marketing context is expected.

Hands-on Senior Cloud Architect focused on GenAI and ML within DoiT's Forward Deployed Engineering delivery organization. Responsible for designing and implementing production-grade AI/ML solutions on AWS, advising customers on cost, reliability, security, and observability, converting field work into reusable patterns and automation, and embedding in account teams to drive product adoption using DoiT Cloud Intelligence (DCI). Based remotely in Mexico or Colombia (employees) or contractors in other LATAM countries.

NVIDIA seeks an Evaluation/ML-Systems Engineer to design benchmarks, metrics, and protocols and build infrastructure tying results to the runs and code that produced them. Requires 5+ years in ML engineering or evaluation, strong Python engineering for shared infrastructure (experiment tracking and data pipelines), and experience designing statistically sound comparisons. Familiarity with security evaluation and measuring agent/LLM behavior is a plus. Base salary range: 152,000–241,500 USD/year.

NVIDIA seeks a Distinguished Engineer to found and lead the AI Safety & Security Engineering team, owning core harness architecture, baseline engineering standards, and the Find/Validate/Patch roadmap. The role requires mentoring founding engineers, bridging research to production, and strong experience (Bachelor's or equivalent and 18+ years) in architecting distributed systems, ML pipelines, or large-scale platforms. Base salary range: 320,000 USD - 488,750 USD.

Lead hiring, coaching, and delivery for the Find, Validate, and Patch engineering roadmap across harness/platform engineering, security research, and evaluation. Requires 12+ years in software engineering (including 5+ years managing teams) and technical depth in ML or systems architecture, security research, and building distributed or platform systems.

Role focused on designing, implementing, and maintaining an agent harness and the systems to run and reproduce experiments for AI safety and security. Requires 5+ years software engineering experience, strong Python skills, familiarity with containerized environments and CI/CD, and experience with agent frameworks/ML infrastructure (NeMo experience is a plus). Base salary range: 152,000 USD - 241,500 USD.

Twilio seeks a Senior Principal Field Architect to act as a technical leader on the Field CTO team, engineering integrations between Twilio Agent Connect and Conversations suite and major AI hyperscaler platforms, building partnerships, supporting sales and GTM, and translating field insights into product strategy. Requires 10+ years engineering experience (and specified enterprise strategy experience), ~20% travel, and is remote‑US with some local hiring exclusions. Salary ranges provided for various US locations.

Work on product security, content safety, ML fairness, and robustness for LLMs and multimodal models. Responsibilities include developing datasets and models, researching and implementing bias detection/mitigation, defining safety metrics, and contributing to MLOps and safety tooling. Requires a Master's/PhD or equivalent, at least 2 years' production ML experience, and hands-on Python experience with frameworks such as PyTorch or Keras.

NVIDIA is hiring a Senior Deep Learning Scientist to develop, train, fine-tune, and deploy large language and multimodal agentic models (audio-visual, voice chat, tool use). Responsibilities include advancing post-training and alignment methods (instruction tuning, preference optimization, RLHF/RLVR/MOPD), agentic reasoning and planning, dataset collection and benchmarking, and scaling models on distributed infrastructure. Qualifications include a Master’s/PhD (or equivalent) and 8+ years relevant experience, strong Python and PyTorch skills, foundation model and RL knowledge, and hands-on multimodal/post-training experience.

Twilio seeks a Sr. AI Architect to set long-term AI/ML architectural vision, own the ML/AI Ops platform roadmap, and transition research into production-grade conversational AI systems (LLMs, RAG, embeddings, vector stores, agentic AI). Role requires deep experience in ML/Ops and LLM Ops, cloud services (AWS/GCP/Azure), and at least 15 years in software engineering (6+ years on production ML platforms). Remote within the United States; ~5% travel anticipated.

Join Reddit's Ads ML Platform team to build large-scale data infrastructure and frameworks for batch and real-time feature computation, feature governance (lineage, validation, drift detection, monitoring, versioning), and agentic/automated ML workflows. The role requires experience operating production ML platform infrastructure, distributed systems, Spark/PySpark/Scala, and driving architecture for high-scale ML systems supporting ads ranking, targeting, and optimization.

Capital One seeks a Distinguished AI Engineer to design, develop, test, deploy, and support foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. Role requires strong software and ML engineering skills (Python, Go/Scala/Java, PyTorch, Hugging Face, VectorDBs, cloud platforms) and experience optimizing training and inference for performance and cost. Qualifications include Bachelor's +8 years or Master's +6 years; visa sponsorship may be considered. Salary ranges provided by location.

DigitalOcean seeks a Staff Engineer (Inference Optimizations) to lead benchmarking and performance work at the inference engine and GPU-kernel level. Responsibilities include attention-layer and kernel optimizations, memory/precision management, multi-node GPU parallelization, and deploying quantization techniques. Requires 5+ years in HPC or AI infrastructure and deep experience with NVIDIA/AMD GPUs, CUDA/ROCm, Triton/CUDA kernels. Compensation range $191,200–$239,000/year.

DigitalOcean seeks a Staff Engineer to lead architectural and low-level performance work for AI inference: benchmarking, GPU kernel optimization, attention-layer and memory/precision management, kernel fusion, quantization (FP8/INT8/FP4), and multi-node GPU parallelization. Requires deep GPU hardware/software expertise (NVIDIA/AMD, CUDA, ROCm, Triton) and 5+ years in high-performance computing or AI infrastructure.

Lead technical work on benchmarking and optimizing inference engines and GPU kernels to maximize throughput and minimize latency for large models. Responsibilities include attention-layer and memory optimizations, quantization (FP8/INT8/FP4), kernel fusion, multi-node GPU parallelization, and advising on GPU hardware/software stacks (CUDA, ROCm, Triton). Requires 5+ years in high-performance computing or AI infrastructure. Salary range provided.

DigitalOcean is hiring a staff/senior engineer to drive architectural decisions and implement performance optimizations at the inference engine and GPU kernel layers. Responsibilities include attention-layer and kernel optimizations, quantization (FP8/INT8/FP4), multi-node GPU parallelization, and benchmarking across NVIDIA and AMD stacks (CUDA, ROCm, Triton). Requires 5+ years in high-performance computing or AI infrastructure and deep GPU/low-level optimization experience.

Join DigitalOcean's AI Inference Data Plane team as a senior engineer to lead design and implementation of distributed, Kubernetes-native inference hosting (LLM serving) using tools like llm-d/vLLM and inference engines such as TensorRT. The role focuses on performance optimization (KV-cache locality, continuous batching, prefix caching), operational excellence (SLOs, observability), mentoring, and contributing to upstream open-source inference projects. Compensation range: $139,200–$174,000 (annual).

The role involves technical leadership and hands-on development of resilient, high-scale data plane services for hosting large generative AI models. Responsibilities include system architecture, performance optimization (tensor/data parallelism, KV-cache optimizations), building on Kubernetes-native inference frameworks (llm-d, vLLM, Ray Serve, etc.), operating critical services with observability and SLOs, contributing upstream to open-source inference projects, and mentoring junior engineers. Required skills emphasize distributed inference, LLM-serving knowledge, and proficiency in Go or Python.