Role to design and build end-to-end ML systems for ranking, retrieval, and personalization (data pipelines, feature engineering, model training/evaluation, production serving); drive relevance through rigorous experimentation; collaborate with Product, Engineering, Data, and Security; requires demonstrated production experience with recommendation/search systems and strong ML engineering and software engineering skills. Authorized to work in the United States without sponsorship.

Lead and scale an engineering team building and optimizing open-source GPU-accelerated deep learning inference frameworks (vLLM, SGLang, FlashInfer). Responsibilities include driving roadmap and execution for Client AI inference frameworks, partnering with compiler/libraries/research teams, performance tuning and profiling of LLMs and multimodal models, and guiding best practices for CUDA, Triton, CUTLASS and multi-GPU communications (NCCL, NVSHMEM). Requires MS/PhD or equivalent, 6+ years software development experience (3+ years technical leadership), strong C/C++ skills, hands-on GPU programming and proven experience deploying/optimizing deep learning models in production. Salary range provided: 184,000–356,500 USD/year.

Role at NVIDIA to lead architecture and performance work on Dynamo, building integrations with vLLM, SGLang, and TensorRT-LLM; responsibilities include finding and removing bottlenecks across runtimes, kernels, networking, and orchestration, and developing inference optimizations such as scheduling, disaggregation, KV caching, and autoscaling. Requires 3+ years experience and strong skills in Python/Rust/C++ and ML inference techniques.

NVIDIA is seeking an engineer to research, prototype, and implement systems optimizations at the intersection of deep learning frameworks and low-level CUDA. Responsibilities include designing and optimizing custom CUDA kernels, architecting distributed cluster-scale systems, analyzing hardware-software interactions, developing profiling and runtime tools, and collaborating with researchers and compiler/driver teams. Requires a BS/MS/PhD or equivalent, 2+ years relevant experience, strong C++ and Python skills, familiarity with CUDA and GPU architectures, and experience with transformers and distributed ML.

Work on research-oriented projects at the intersection of CUDA and deep learning systems, including custom high-performance CUDA kernel development, profiling and optimizing generative AI models and transformers, and architecting distributed systems that scale from single GPUs to supercomputer clusters. Requires strong C++ and Python skills, deep learning background, GPU/CUDA experience, and 8+ years of relevant experience.

As an MLOps Engineer you will design and evolve production ML lifecycle systems (experiment tracking, artifact management, versioning, lineage, promotion workflows), build operational infrastructure for LLM/agentic systems, design evaluation and monitoring frameworks, and build large-scale training pipelines. Role requires 5+ years of software/MLOps/ML platform engineering experience, strong Python engineering, and experience with platforms like Databricks, Spark, Delta Lake and MLOps frameworks such as MLflow/Metaflow/Kubeflow.

Work on designing and building Astronomer’s global context layer for data, focusing on search, retrieval, semantic search, code generation, and applied AI using LLMs and embeddings. Requires 5–8 years of software engineering experience (Python or Go). Hybrid position with at least 3 days/week in the New York City office. Estimated total compensation $210,000–$250,000.

Lead development of core platforms that process large volumes of network and operational data to power AI experiences and agentic systems. Responsibilities include architecture and hands-on implementation of distributed, real-time, cloud-native microservices and data pipelines, mentoring engineers, and ensuring reliability, observability, and security for production deployments.

Lead design and delivery of scalable, secure, observable distributed systems and AI/agentic platforms for intelligent networking. Requires 10+ years software lifecycle experience, 5+ years programming (Python/Java/Go/C++), 3+ years designing large-scale distributed systems on cloud platforms, and experience with stream processing, network telemetry, and production operations.

CrowdStrike is hiring a Senior Security Researcher II on the Counter Adversary Operations team to manage large-scale collection infrastructure, design and implement AI/LLM-powered automation and agent workflows, perform threat intelligence research on underground ecosystems, and respond to customer-impacting collection and data-quality incidents. The role emphasizes web data collection, OPSEC tradecraft, production deployment (Docker/cloud), APIs, and collaboration across global teams.

Primer is hiring a Data Engineer III to design and build reliable, tested, maintainable data systems that support analytics, product features and machine learning. The role works with Python and SQL across batch and streaming (including CDC) pipelines, modern data warehouses (Snowflake), transformation tooling (dbt), and cloud-native infrastructure (AWS, Kubernetes, Helm, Terraform). The position is remote-first and listed for candidates in the UK, Hungary, Poland, South Africa, Portugal, Ireland and Romania.

Senior Data Engineer + AI (remote) responsible for designing, developing, and maintaining AI-powered applications, scalable backend services, and cloud-native data platforms. Key technologies: Python, SQL, TypeScript, AWS, Databricks, Apache Spark, dbt, LLMs. Responsibilities include building end-to-end data pipelines, ensuring data quality/governance/observability, developing production-ready LLM/AI solutions, and collaborating with cross-functional teams. Requires 7+ years in software/data/AI engineering and a relevant bachelor's degree or equivalent experience.

Telecommuting (U.S.) Senior Data Engineer role at Red Hat responsible for building distributed data pipelines using PySpark and dbt, orchestrating workflows with Apache Airflow, administering Databricks and cloud storage IAM, implementing retrieval and ML systems (NER, XGBoost, Keras, Transformers), operationalizing MLOps with MLflow, managing CI/CD and containers (Git, Tekton, buildah, skopeo) and deploying on Red Hat OpenShift. Salary range stated: $158,309–$180,000/year. Education/experience paths described in the posting (Master's + 3 years or Bachelor's + 5 years).

Cloudera seeks a senior-level Forward Deployed AI Engineer to work within the Forward Deployed Engineering (FDE) team in Japan and South Korea, building full-stack ML and agentic applications, advising customers on AI architecture and deployments, and codifying repeatable solution patterns. Requires 7+ years building production-grade systems, including 2–4 years on ML/GenAI systems, and experience with foundation models, RAG, LLMOps/MLOps, and cloud or big-data technologies.

Embed with strategic customers to design, prototype, and ship full-stack AI/ML and agentic solutions on Cloudera. Requires 7+ years building and deploying production-grade systems (including 2–4 years on ML/GenAI systems), experience with foundation models, RAG, LLMOps/MLOps, model serving/observability, and enterprise AI architecture.

Thorn seeks a Senior ML Engineer to own end-to-end model development and deployment for computer vision and natural language tasks that support victim identification, content removal, and abuse prevention. The role is remote (US-based), involves some travel, and requires at least 5 years of ML/AI experience and experience deploying production ML systems. Technologies listed include Python, PyTorch, TensorFlow/Keras, Hugging Face, FAISS, ONNX, Kubernetes, AWS, Terraform, CI/CD, OpenCV, and related tooling.

Quora is hiring a new-grad Software Engineer for the Machine Learning Platform team to build and maintain infrastructure for production ML models (including LLMs), improve GPU model serving performance and cost, modernize the ML ecosystem and feature store, and improve ML developer velocity. Stack mentioned includes Python, Go, C++, PyTorch, Kubernetes/EKS, NVIDIA Triton, Ray, and AWS. Role is remote for candidates in the United States and Canada and expects availability during Quora's coordination hours (Mon–Fri 9am–3pm PT).

Join NVIDIA's Infrastructure Specialists team to set up, tune, and validate AI factory environments across multi-GPU/multi-node Linux clusters. Responsibilities include running and analyzing AI/LLM benchmarks, diagnosing failures/hangs/low performance, applying observability and automation (Python/Shell) for benchmarking and regression checks, and collaborating with hardware/software/network/product teams. Requires 5+ years managing Linux systems in HPC/distributed/AI environments and hands-on experience with multi-GPU or multi-node AI/ML workloads and NCCL/collective communication patterns.

Lead principal-level architect for The Home Depot's Mobile App Renovation Strategy (MARS), defining a modular, high-performance mobile ecosystem and driving AI-first development. Responsibilities include cross-functional platform leadership, POC development, architecture for Kotlin Multiplatform, SDUI, GraphQL, and backend systems, mentoring engineers, and acting as an escalation point. Requires 7+ years relevant experience and authorization to work in the United States.

NVIDIA seeks a Senior Solutions Architect with 6+ years in AI infrastructure, HPC, networking, or SRE to design, profile, and optimize large-scale GPU clusters (on-prem and cloud). Responsibilities include troubleshooting GPU networks (InfiniBand, RoCE, RDMA), debugging NCCL, leading POCs, and partnering with engineering and sales. Remote work is supported; occasional travel (~20%) required.