Weights & Biases
Data AI · ML experiment tracking
Weights & Biases currently has 47 active AI-related job listings. The majority of these roles, 51%, are focused on serving infrastructure, with an additional 34% dedicated to agents. Engineering is the primary function being hired for, with the United States being the dominant hiring country. The company is frequently seeking candidates with experience in model serving, inference infrastructure, and LLM observability. Over the last 30 days, there has been a 75% decrease in new AI roles posted, with 4 new positions compared to 16 in the preceding 30-day period.
Currently tracking 35 active AI roles, down 14% versus the prior 4 weeks. Primary focus: Serve · Engineering. Salary range $92k–$341k (avg $211k).
Data AI · ML experiment tracking
Weights & Biases currently has 45 active AI-related roles in our index. The most common open titles are: Account Solution Architect (5), Account Solutions Architect - Greenfield (2), Account Solution Architect - Financial Services, Applied AI Engineer, Inference, Forward Deployed Engineer, AI Agents. Most positions are in Engineering and Product.
Weights & Biases's active AI hiring is concentrated in: serving infrastructure (51%), agents (38%), application (4%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Weights & Biases is hiring AI talent in: United States (43 roles), United Kingdom (2 roles), Canada (1 role).
Job postings at Weights & Biases most frequently mention: GPU Computing, Kubernetes, Production ML Systems, ML Ops, Storage Systems.
In the past 30 days, Weights & Biases has posted 5 new AI-related roles. That is a -50% change versus the prior 30 days (10 → 5).
| Title | Stage | AI score |
|---|---|---|
| Senior Software Engineer - GPU Kernel Authoring & Optimization Senior Software Engineer focused on authoring and optimizing GPU kernels for large-scale LLM inference serving. The role involves deep understanding of GPU architecture, CUDA programming, and performance benchmarking to achieve maximum throughput and minimum latency. Responsibilities include kernel development, optimization, benchmarking, and contributing to the inference stack's performance and reliability. | Serve | 9 |
| Applied AI Engineer, Inference Applied AI Engineer focused on optimizing and benchmarking the inference serving platform for AI models, working on latency, throughput, and reliability. | Serve | 8 |
| Principal Engineer - Perf and Benchmarking Principal Engineer role focused on leading the Benchmarking & Performance team at CoreWeave, a cloud provider for AI. The role involves defining strategy, leading end-to-end MLPerf submissions (Training & Inference), designing and implementing a Kubernetes-native benchmarking service for latency and throughput, and building CI/CD pipelines for scale. It requires deep expertise in distributed systems, GPU performance, model-serving stacks, and Kubernetes, with a focus on achieving industry-leading performance data and publications. |
| ServeEval Gate |
| 8 |
| Technical Program Manager, Inference CoreWeave is seeking a Technical Program Manager (TPM) focused on inference to join their AI/ML Platform Services team. This role will drive end-to-end program management for inference platform initiatives, including reliability, customer onboarding, launch readiness, and runtime optimization. The TPM will lead cross-functional programs to ensure the successful delivery of scalable, reliable, and high-performance inference services, working closely with engineering, product, and infrastructure teams to improve how these services are launched, onboarded, operated, and optimized. The role requires strong technical fluency in distributed inference systems, GPU compute, and cloud-native architectures, with a focus on measurable improvements in reliability, performance, and customer delivery. | Serve | 7 |
| Technical Program Manager - Performance & Benchmarking This role is for a Technical Program Manager focused on Performance & Benchmarking within an AI/ML Platform Services organization. The TPM will drive end-to-end program execution for initiatives related to infrastructure validation, performance testing, benchmark execution, and observability, ensuring CoreWeave's infrastructure is performant and stable for AI workloads. The role involves partnering with engineering, infrastructure, product, and go-to-market teams to improve workload performance, validate new environments, and create visibility into system performance. | Serve | 7 |
| Solution Specialist, AI Runtime Services This role focuses on bringing new AI runtime services, such as model serving and sandboxes, to market. It involves driving initial customer adoption, gathering feedback for the product roadmap, and enabling sales teams to position these services. The role requires deep expertise in AI runtime infrastructure, including serving frameworks, inference optimization, and execution isolation. | Serve | 7 |
| Staff Software Engineer, Cluster Orch (SUNK) Staff Software Engineer role focused on advancing CoreWeave's orchestration platform (SUNK - Slurm on Kubernetes) for AI training and inference at scale. The role involves technical leadership, architectural direction, and ensuring efficient, reliable workload execution across large GPU clusters. | Serve | 7 |
| Account Solution Architect Account Solution Architect for CoreWeave, focusing on AI/ML infrastructure and MLOps solutions for customers in Northern EMEA. The role involves technical discovery, solution design, proof-of-concept engagements, and acting as a customer advocate to internal teams. Requires strong knowledge of ML training/inference, MLOps platforms, and underlying infrastructure like GPUs, networking, and Kubernetes. | ServeData | 7 |
| Staff Software Engineer, Inference Staff Software Engineer on the Inference Platform Team at CoreWeave, focusing on building and operating a Kubernetes-native inference platform for AI workloads. The role involves technical leadership in architecture, performance optimization (latency, throughput, GPU utilization), and system reliability for low-latency, high-throughput systems at massive scale, with deep work in distributed systems and Kubernetes infrastructure. | Serve | 7 |
| Staff Technical Program Manager - Cluster Orchestration & Applied Training Staff Technical Program Manager to lead cross-functional programs for AI/ML Platform Services, focusing on Cluster Orchestration (scheduling, launching, managing AI workloads) and Applied Training (enabling researchers to use infrastructure for pre-training, fine-tuning, RL, evaluations). The role involves partnering with engineering, product, and research teams to improve workload execution and user interaction with training platforms, driving delivery across various AI training workflows and ensuring successful launches and operational ownership. | ServePost-train | 7 |
| Principal Engineer, Cluster Orchestration CoreWeave is seeking a Principal Engineer to lead the design and evolution of their AI infrastructure's cluster orchestration systems, including Slurm, Kubernetes, and SUNK. This role involves defining long-term architecture, solving scaling problems, and ensuring the reliability and efficiency of GPU resource utilization for AI training and inference workloads. | Serve | 7 |
| Senior Software Engineer I, Inference CoreWeave is seeking a Senior Software Engineer to own and improve their Kubernetes-native inference platform, focusing on latency, throughput, and reliability. The role involves leading design, implementing optimizations, strengthening incident posture, and mentoring junior engineers. Requires experience with distributed systems, Kubernetes, and inference internals. | Serve | 7 |
| Sr. Software Engineer - Perf and Benchmarking Senior Software Engineer focused on performance and benchmarking of AI infrastructure, including Kubernetes-native services, MLPerf runs, and model-serving stacks. The role involves building and improving services to measure latency, throughput, and cost, and ensuring reproducible benchmarking processes. | ServeEval Gate | 7 |
| Sr. Engineering Manager, Inference Senior Engineering Manager for AI/ML Platform team at CoreWeave, focusing on productizing and operating their inference offering. The role involves leading a team to ensure service reliability, observability, operational excellence, and developer experience for AI workloads. Responsibilities include roadmap execution, engineering processes, cross-functional partnerships, and building a culture of technical excellence. | Serve | 7 |
| Software Engineer, Inference AI/ML Software Engineer focused on improving the latency, reliability, and cost of model serving on a GPU platform, working with services like Triton, vLLM, and TensorRT-LLM. | Serve | 7 |
| Senior Software Engineer II, Inference Senior Software Engineer II focused on owning and optimizing CoreWeave's Kubernetes-native inference platform to meet strict P99 SLAs at scale. Responsibilities include leading design reviews, implementing advanced optimizations for latency and throughput, strengthening incident posture, and mentoring junior engineers. Requires strong experience in distributed systems, Python/Go, networked systems performance, Kubernetes, and ML inference internals. | Serve | 7 |
| Senior Systems Engineer, OS Automation Senior Systems Engineer focused on automating and scaling Linux OS and Kernel build pipelines, with a strong emphasis on integrating AI/ML technologies like LLMs, RAG, and predictive modeling to create AI-native infrastructure, smart CI/CD, auto-remediation, and predictive regression detection. | ServeAgent | 7 |