Remote jobs in the United States

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Added 4 mins ago
AI Engineer
CACI, INC.-FEDERAL
Remote, United States
…workflows and agents on an enterprise AI workflow management platform supporting the Department of the Air Force. You will work directly with the AI Platform Architect to turn platform…
Added 9 mins ago
Senior Back-End Engineer - LATAM
Virtasant
Remote, United States
…program in healthcare operations and workforce decisioning. The platform helps operations leaders understand what is happening across their workforce, make informed decisions, take action…
Added 17 mins ago
Lead Director Product Membership
Oak Street Health MSO LLC
Remote, United States
EHR & Platform Integration: Partner with Epic Analysts, platform architects, and core Salesforce teams to ensure seamless data flow between frontline clinical workflows in Epic and…
Added 29 mins ago
Senior Sales Executive
Doyon Limited
Remote, United States
…Microsoft Dynamics 365 (Finance, Sales, Customer Service, Power Platform), Microsoft 365, Microsoft Azure, and additional sales opportunities for recurring support/managed services and…
Added 52 mins ago
Director of Data (P&C Insurance)
Sutton National Insurance Company
Remote, United States
Define KPIs and metrics to measure data quality, platform performance, and adoption, reporting progress and strategic updates to executive leadership.
Added 1 hour ago
Senior Data Scientist - GenAI
CVS Health
Remote, United States
…evaluation, while one-third focuses on software engineering, platform integration, API development, and production implementation. Lumina is CVS Health's internal enterprise knowledge and…
Added 1 hour ago
Principal Engineer, Model Performance
Runware
Remote, United States
Runware is the AI inference platform that builds and runs its own infrastructure, end to end. Our Sonic Inference Engine has served more than 20 billion requests for over 1 million…
Added 2 hours ago
Mechanical Engineer
Motive
Remote, United States
…single system. Combined with industry leading AI, the Motive platform gives you complete visibility and control, and significantly reduces manual workloads by automating and simplifying…
Added 2 hours ago
J
Sr. Systems Engineer – AI Gateway Platform
Jobgether
Remote, United States
- $125,000 to $180,000 USD / year
Identify platform bottlenecks, streamline integration workflows, and continuously improve gateway operations.
Added 3 hours ago
Technical Support Engineer (CS)
Jobgether
Remote, United States
The Technical Support Engineer will play a key role in helping enterprise customers successfully adopt and operate a platform that connects AI agents and human users with business systems…
Added 4 hours ago
AI Enablement Lead
UFORCE
Remote, United States
…command-and-control layer that operates them together. Each platform is deployable on its own, and stronger as part of the system. Its product lines include the MAGURA family of uncrewed…
Added 6 hours ago
Test Manager - Output/CCM/Document Management Systems
Jobgether
Remote, United States
In this 50% part-time freelance role, you will define and oversee the testing strategy, ensuring that the new platform delivers accurate and reliable document outputs.
Added 7 hours ago
Solution Architect
Jobgether
Remote, United States
Identify and resolve architectural challenges, technical dependencies, integration constraints, and cross-platform issues.
Added 7 hours ago
Lead Systems Design Engineer
Jobgether
Remote, United States
You will oversee the design, development, debugging, verification, and validation of platform firmware solutions.
Added 7 hours ago
J
Full-Stack Platform Engineer
Jobgether
Remote, United States
- $190,000 to $215,000 USD / year
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Full-Stack Platform Engineer based in the United States.
Added 7 hours ago
J
Enterprise Applications Architect
Jobgether
Remote, United States
- $116,860 to $155,995 USD / year
…operational support. You will define future-state architectures, integration standards, lifecycle roadmaps, and environment strategies that support business objectives. Working closely with…
Added 7 hours ago
J
Director, People AI Engineering & Innovation
Jobgether
Remote, United States
- $122,400 to $204,400 USD / year
AI Strategy and Technical Roadmap: Define and evolve the People organization’s AI strategy, architecture, platform direction, and capability roadmap, translating business priorities and…
Added 7 hours ago
Full Stack Developer
Jobgether
Remote, United States
Familiarity with Microsoft Power Platform, Power Automate, and the integration of large language models and generative AI into software solutions.
Added 8 hours ago
Sr. Software Technical Support Manager
Jobgether
Remote, United States
Identify technical requirements, system impacts, and integration dependencies during early software planning stages.
Added 9 hours ago
Product Manager, Identity
Tailscale
Remote, United States
…Nearly every enterprise deployment begins with an identity integration, grows through complex multi-IdP setups, and increasingly depends on automated lifecycle management for production…
Added 9 hours ago
Product Manager, Identity
Tailscale
Remote, United States
…Nearly every enterprise deployment begins with an identity integration, grows through complex multi-IdP setups, and increasingly depends on automated lifecycle management for production…
Added 9 hours ago
Product Manager, Networking Features
Tailscale
Remote, United States
This is the most user-visible role in Tailscale's Dataplane Platform, and the work is as much product design as it is networking. DNS settings, connector topologies, and service definitions…
Added 9 hours ago
Product Manager, Networking Features
Tailscale
Remote, United States
This is the most user-visible role in Tailscale's Dataplane Platform, and the work is as much product design as it is networking. DNS settings, connector topologies, and service definitions…
Added 9 hours ago
J
Solution Consultant
Jobgether
Remote, United States
- $95,000 to $130,000 USD / year
In this role, you will drive the adoption of innovative healthcare integration and interoperability solutions by helping organizations overcome complex data exchange challenges. You will…
Added 10 hours ago
FL
Senior Product Manager, Integrations and New Verticals
Figure Lending
Remote, United States
- $183,600 to $275,400 USD / year
…partners depend on. You’ll build the monitoring that makes integration health visible across the company and use funnel, conversion, and quality data to decide where the next investment…

Runware

Principal Engineer, Model Performance

Remote, United States

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Job details

Posting language: English
Posted: Nov 6, 2026

Original job description

Runware is the AI inference platform that builds and runs its own infrastructure, end to end. Our Sonic Inference Engine has served more than 20 billion requests for over 1 million developers and 500 million end users, with 400,000+ models behind a single integration, at up to 10x lower cost per token than traditional providers. We are now building the AI Factory that runs it. The Sonic Inference Pod packs 1 MW of custom-designed compute into a 20-foot container with closed-loop, water-free cooling, sited wherever power exists. Pods are live in the US and Europe, and we are scaling to dozens of pods and tens of thousands of GPUs, all operated as one distributed fabric that reroutes traffic the moment a pod goes offline (announcement). Every request that hits that fleet, whether it is an image, a video, a voice or a token stream, has to come back faster and cheaper than anyone else can serve it. Model performance is what makes that true. That is the job. The role As Principal Engineer, Model Performance, you will own how fast and how cheaply every model on Runware runs: diffusion and video generation, speech, 3D and LLMs, across 400,000+ models and tens of thousands of GPUs. You will set the performance roadmap, build the hardest pieces with your own hands, and build and lead the Model Performance team as it grows around you. This is a principal-level role for someone who has led inference performance work at the frontier and still writes the kernel. You will decide where the next 2x comes from on a given model and hardware generation, whether that is a fused attention kernel, a better quantization recipe, speculative decoding, a smarter batching policy or a different parallelism layout, and then make it land in production on real traffic. You will work directly with the Sonic Inference Engine team, the infrastructure and hardware teams, and with NVIDIA and the open-source engine communities, and you will hire, mentor and lead the engineers who do this work alongside you. Success means Runware serves a new open model at the Pareto frontier of latency and cost within days of its weights being released, our cost per request keeps falling with every hardware generation, and the team you have built can do this without you in the loop. What you'll do

Own inference performance end to end for the fleet: the kernels, the serving engines, the model-level optimizations and the benchmarks that prove them, across image, video, audio, 3D and LLM workloads on every GPU generation we run.
Set the model performance roadmap. Decide which models, hardware and techniques get the team's attention and in what order, based on real traffic, real cost and what the next generation of pods will run.
Do the hardest work yourself: write and tune CUDA kernels, fuse attention and MLP paths, bring up new quantization formats (FP8, FP4, INT4) with quality held, and get new parallelism and batching strategies working on multi-GPU nodes.
Make new models fast on day one. Build the pipeline that takes a newly released open model from weights to a production-grade, optimized deployment in days, and keep closing that gap.
Choose and shape the serving stack: TensorRT-LLM, vLLM, SGLang, custom diffusion and video pipelines, and the Sonic Inference Engine's own runtime. Decide what we adopt, what we fork and what we write ourselves, and contribute upstream where it pays.
Own the benchmarking and performance regression system: reproducible, hardware-aware measurement of throughput, latency, cost and quality for every model we serve, wired into CI so that a regression never reaches a pod.
Partner with infrastructure and hardware engineering on GPU memory, storage and network bottlenecks that show up as inference latency, and feed what you learn back into the next generation of servers and pods.
Build and lead the team. Hire principal and senior engineers, set the bar for technical rigour, mentor the people on the team, and run it so that a very small group delivers performance across a very large model catalogue.
Use AI to accelerate the work: automated kernel search and tuning, benchmark generation, profiling triage and documentation with LLM-based agents, so that the team's output grows faster than its headcount.

Requirements

What we're looking for

10+ years in GPU, HPC or deep learning systems engineering, with several of those optimizing inference performance for models in production at a company that runs them at scale.
A track record of shipping performance, not just measuring it. You have taken a state-of-the-art model from a reference implementation to the Pareto frontier of latency and cost on real hardware, and you know what breaks between the two.
Deep, current, hands-on CUDA and GPU architecture expertise: kernel design, memory hierarchy and occupancy, Tensor Cores, fused kernels, CUDA Graphs, NCCL, and the profilers (Nsight Systems and Compute) that show exactly where a microsecond goes.
Real production experience with at least one major inference engine (TensorRT-LLM, vLLM, SGLang or similar) and with the techniques that define modern serving: continuous batching, paged KV cache, speculative decoding, prefill/decode disaggregation, quantization and tensor, pipeline and expert parallelism.
Fluent in Python and C++, comfortable in PyTorch internals, torch.compile and Triton, and happy to write the benchmark, the kernel and the CI job yourself rather than waiting for someone else to.
Experience leading engineers: you have built or run a performance team, hired for it, set its technical direction and stayed hands-on while doing so.
You use AI to accelerate your own output every day, for kernel search, profiling analysis, benchmarking, documentation and code review, and you have a clear view of how a small team armed with these tools should operate differently.
Comfortable owning outcomes in a fast-moving, ambiguous environment, making decisions with incomplete information and being accountable for latency, cost and quality across hundreds of thousands of models.

Nice to have

Diffusion and video generation performance: DiT and UNet pipelines, attention at long sequence lengths, step distillation, caching across denoising steps, LoRA hot-swapping, and the loaders and samplers in ComfyUI, Diffusers or custom engines.
Contributions to TensorRT-LLM, vLLM, SGLang, FlashAttention, CUTLASS, Triton, Dynamo or similar open-source inference projects, or an open-source project of your own that people run.
Experience with Blackwell-generation hardware (B200, GB200/GB300 NVL72), NVLink and NVSwitch topologies, and multi-node inference over InfiniBand or RoCE.
Mixture-of-experts serving: expert parallelism, expert placement and load balancing, and the memory and communication trade-offs that come with them.
Accuracy evaluation for optimized models: the harnesses, datasets and statistical discipline to prove a quantized or distilled model is as good as the original.
Experience with non-NVIDIA accelerators (AMD, TPU or custom silicon) and with porting an inference stack across them.
Speech and audio model serving: streaming ASR and TTS with tight latency budgets.
Published work, patents or talks on inference performance.

Benefits

What we offer

A rare mandate: own inference performance for one of the largest model catalogues in the world, on hardware the company designs and operates itself, at a business whose margin is your work, with the GPU budget and backing to match.
Meaningful stock options.
We're a remote-first collective, meeting in person twice a year to plan, brainstorm and celebrate wins. We keep core hours for collaboration and calls; outside those, you set your own schedule.
Our release cycles are fast and intense, and they're followed by real downtime. We expect you to take it.
Generous paid time off, including vacation, sick days and public holidays.
Paid maternity, paternity and caregiver leave.
Twice-yearly company retreats in inspiring locations.

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