Role focuses on building performance testing frameworks, automated CI/CD pipelines, benchmarking systems, and dashboards to track and analyze GPU and compiler performance across models and hardware. Requires 5+ years software engineering experience, strong Python (C++ a plus), familiarity with deep learning frameworks (PyTorch/TensorFlow/JAX/TensorRT), GPU/hardware-aware performance analysis, profiling, and debugging across software and hardware layers. Base salary range listed: 152,000 USD–241,500 USD.

The role owns vector stores for RAG, the feature store for training and inference, and graph data structures modeling applicants/products/decisions. Responsibilities include data discovery and profiling, building AI-ready datasets with lineage and freshness SLAs, evaluating retrieval/feature quality, and partnering with ML engineers and governance teams. Requires 4+ years of relevant experience and strong skills in Python, SQL, Databricks, vector & graph technologies, and embedding/LLM tooling.

Owner of the internal data warehouse and analytical data layer: design, build and maintain transformation pipelines, define schemas and data contracts, implement data quality, lineage and observability, and collaborate with analysts and stakeholders to enable BI and AI workloads. Requires 10+ years of data engineering experience, strong SQL and Python skills, experience with modern warehouses (Snowflake/BigQuery/Redshift), AWS data services, dbt, Airflow and working remotely while being located in Europe.

Work involves building high-performance runtime and compiler components for inference (LPX), implementing mappings for large-scale inference workloads, integrating with NVIDIA software ecosystem, and benchmarking and profiling for performance. Candidates should be pursuing or recently completed an MS/PhD (or equivalent), have systems-level programming experience (C/C++ and/or Rust), and hands-on experience with compiler/runtime development (LLVM/MLIR, IR design, optimization passes) and deep learning frameworks (TensorFlow, PyTorch, ONNX).

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.

Headspace is hiring a Staff Machine Learning Engineer on the Personalization team to design, implement, and ship production-ready personalization systems (recommendation, vector search/embeddings, RAG/LLM orchestration, conversational AI, knowledge graph). The role requires 5+ years of ML engineering experience, strong Python and ML framework skills (PyTorch/TensorFlow/scikit-learn), experience with modern NLP tools, testing and version control, and familiarity with AWS (SageMaker, Lambda, S3, DynamoDB, IAM). Candidates must permanently reside in the United States. Posted as a full-time position with a stated annual base salary range.

Role responsible for building and improving security-focused ML models (guardrails, classifiers, anomaly detection) across Reddit's GenAI workflows. Owns full ML lifecycle including data ETL, feature engineering, training, evaluation, deployment, monitoring, and retraining. Requires 5+ years of production ML experience and hands-on experience with frameworks such as PyTorch or TensorFlow; remote (United States) position.

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.

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.

Senior individual contributor responsible for architecture and engineering of ads identity modeling and related measurement ML solutions. Requires designing and deploying large-scale ML systems (model training, inference, feature engineering), collaborating across product, data science, privacy and legal, and mentoring engineers. Minimum 7+ years software engineering experience with 3+ years on ML-driven systems; salary range $230,000–$322,000 USD/year.

Remote role open to applicants in the US, Canada, and the EU. Requires 5+ years in product/engineering leadership in SaaS/AI/platform environments with hands-on coding, architecture, POC development, go-to-market enablement, team building, and external evangelism responsibilities.

NVIDIA is hiring a Senior Sensor Fusion Engineer to develop core functionality for autonomous driving by fusing perception DNNs and map signals into real-time 3D world models. The role focuses on enabling HD mapless urban driving and L3 highway autonomy using camera, lidar, and radar inputs, building occupancy grids and occlusion masks, and producing automotive-quality code. Requires 8+ years' experience (with 2+ years in AV/robotics) and experience on embedded/automotive platforms.

NVIDIA is hiring a new-college-grad engineer to build and maintain high-performance compiler and runtime components for LPX inference, implement mappings for large-scale inference workloads, and benchmark/profile performance. Candidates should be pursuing or recently completed an MS or PhD (or equivalent), have systems-level programming experience (C/C++ and/or Rust), and hands-on experience with compiler/runtime development such as LLVM/MLIR, IR design, and optimization passes.

Senior Solutions Architect responsible for guiding customers on NVIDIA hardware/software for AI and professional graphics workflows. Requires 8+ years software development experience (Python, C/C++), deep learning/CUDA knowledge, familiarity with graphics APIs and GPU architectures, strong Windows/Linux skills, and willingness to travel to customer sites and NVIDIA HQ (Santa Clara, CA).

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.

Work at the intersection of technical support, workflow automation, and applied AI to design and implement agentic AI systems, ticket triage, routing, knowledge retrieval, case summarization, and operational insights. Requires at least 3 years of relevant software, automation, or applied AI experience, strong Python and API skills, and experience building production internal tools; role is remote-first and lists a salary range of 125,000–170,000 USD per year.

Build and optimize inference stacks (vLLM), develop and tune GPU kernels, extend compiler/DSL infrastructure, define benchmarking (including MLPerf), and architect containerized large-scale inference deployments. Requires strong Python and C/C++ skills, GPU/CUDA experience, familiarity with PyTorch and inference engines, container/orchestration experience, and advanced performance engineering; typical experience expectations are 7+ years (BS) or 5+ years (MS).

NVIDIA is hiring for its Deep Learning Compiler (DLC) team to develop compiler optimization algorithms, performance optimizations, and compiler infrastructure for neural networks used across data centers, devices, automotive, and robotics. The role requires 3+ years of relevant work or research experience, proficiency in C/C++ and Python, and familiarity with technologies such as CUDA/OpenCL, MLIR, XLA, TVM, LLVM, and deep learning frameworks like PyTorch. Base salary range: 152,000 USD - 241,500 USD per year.

Product-focused Staff AI Engineer role to design, develop, and deploy AI-powered features using LLMs and multiple AI models. Responsibilities include integrating and orchestrating models, prototyping and iterating on features, ensuring reliability and scalability in production, establishing evaluation metrics, addressing AI privacy/security/compliance, and mentoring engineers. Requires 5+ years of backend and/or full-stack engineering experience and proficiency with Python, JavaScript/TypeScript, relational databases (Postgres/MySQL), and Elasticsearch. Location: United States. Remote tags present.

Join ClickUp as a Staff AI Engineer on the AI Platform team to design, implement, and operate scalable backend services, model serving, orchestration, and MLOps for LLM-powered features. The role is hands-on with multiple LLM providers (OpenAI, Anthropic, Google) and requires expertise in cloud-native technologies (Kubernetes, Docker, AWS/GCP/Azure), distributed systems, backend engineering, and AI privacy/security.