Engineering Manager, AI Models Infrastructure IntercomEngineering Manager, AI Models InfrastructureDublin, CAFounded in 2011, Fin became one of the fastest growing companies and remains one of the largest private software companies in the world with nearly 30,000 global businesses using our products to transform their customer support. Fin can also be combined with our Helpdesk to become a complete solution called the Fin Customer Service Suite, which provides AI enhanced support for the more complex or high touch queries that require a human agent.
Staff Software Engineer, Foundational Model Serving DataBricksStaff Software Engineer, Foundational Model ServingSan Francisco, CA$192,000–$260,000 / yearWe're looking for engineers who have owned high scale operational sensitive systems like customer facing APIs, Edge Gateways, ML Inference, or similar services and have an interest in getting deep building LLM APIs and runtimes at scale. More than 20,000 organizations worldwide - including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 - rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents.
Senior Product Manager, Model APIs & Developer Experience Together Computer IncSenior Product Manager, Model APIs & Developer ExperienceSan Francisco, CA$200,000–$280,000 / yearWe believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. The interfaces around those models shape the entire customer experience: how easily a developer can migrate an application, how reliably an agent can use a model, and how a team runs large asynchronous workloads.
Staff Software Engineer- Foundation Model Inference DataBricksStaff Software Engineer- Foundation Model InferenceSan Francisco, CA$190,000–$265,000 / yearThe impact you will have: Build LLM infrastructure powering large-scale inference workloads for customers through partner models (OpenAI, Anthropic, Gemini) and self-hosted models (Qwen, GPT-OSS, Llama). More than 20,000 organizations worldwide - including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 - rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents.
Engineering Manager - Model Performance BasetenEngineering Manager - Model PerformanceSan Francisco, CaliforniaBy uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. Drive the development and deployment of large-scale optimization techniques for various ML models, especially large language models (LLMs).
NewTechnical Program Manager, Model Performance BasetenTechnical Program Manager, Model PerformanceSan Francisco, CaliforniaExperience program-managing model performance or inference optimization work - you understand how engines like vLLM, TensorRT-LLM, SGLang, or NVIDIA Dynamo fit into a production serving stack and can engage credibly with the engineers building on them. You won't inherit an existing program framework, you'll build one from the ground up: the planning structure, execution processes, metrics and the cross-functional alignment that a fast-growing organization needs.
NewSoftware Engineer - Model Performance BasetenSoftware Engineer - Model PerformanceSan Francisco, CaliforniaBy uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. Implement, refine, and productionize cutting-edge techniques (quantization, speculative decoding, KV cache reuse, chunked prefill and LoRA) for ML model inference and infrastructure.
NewSoftware Engineer - Model Performance Systems BasetenSoftware Engineer - Model Performance SystemsSan Francisco, CaliforniaBy uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. You will not just be building the automated "speedometer and diagnostic" suite for our next-generation AI infrastructure; you will be defining the roadmap, driving key technical decisions, and taking full ownership of the future of this work.
NewSoftware Engineer - Model Products BasetenSoftware Engineer - Model ProductsSan Francisco, CaliforniaDesign, build, and operate the Model APIs surface with focus on advanced inference capabilities: structured outputs (JSON mode, grammar-constrained generation), tool/function calling and multi-modal serving. Profile and optimize TensorRT-LLM kernels, analyze CUDA kernel performance, implement custom CUDA operators, tune memory allocation patterns for maximum throughput and optimize communication patterns across multi-GPU setups.
Research Engineer - Audio & Speech Models ZyphraResearch Engineer - Audio & Speech ModelsSan Francisco, CaliforniaAs a Research Engineer - Audio & Speech Models , you will be a core contributor on Zyphra’s Audio Team, building the next generation of open-source autoencoders, ASR, TTS, SSL, and speech-to-speech models. Expertise and intuition for training models in the audio domain, including text-to-speech, ASR, speech-to-speech, speech-emotion-recognition, or other models.
Research Engineer - Audio & Speech Models Zyphra TechnologiesResearch Engineer - Audio & Speech ModelsSan Francisco, CAThe Role: As a Research Engineer - Audio & Speech Models, you will be a core contributor on Zyphra's Audio Team, building the next generation of open-source autoencoders, ASR, TTS, SSL, and speech-to-speech models. Qualifications / Additional Skills: Expertise and intuition for training models in the audio domain, including text-to-speech, ASR, speech-to-speech, speech-emotion-recognition, or other models.
Staff Product Manager, Model Lifecycle & Management Pinterest IncStaff Product Manager, Model Lifecycle & ManagementSan Francisco, CARemote$164,695–$339,078 / yearAs a Senior Product Manager for Signal Lifecycle within Trust & Safety, you''ll own the product strategy for the ML platform that powers how Pinterest trains, evaluates, deploys, and measures content safety models at scale. What you''ll do: Own and drive the Signal Lifecycle product roadmap, including ML Flywheel infrastructure, auto-deployment, model onboarding, golden dataset management, and signal performance measurement.
Backend Engineer, Models MeterBackend Engineer, ModelsSan Francisco, CaliforniaTo make this possible, we don’t just need great models; we need infrastructure that gives those models clean, versioned, low-latency access to the right data, across training, evaluation, and deployment. As described on Meter.ai , we’re building models in a closed-loop system that takes (as input) real-time telemetry, logs, and events on the network to autonomously troubleshoot, improve performance, and resolve issues.
Modelling Data Scientist, Vice President - AI Labs BlackRockModelling Data Scientist, Vice President - AI LabsSan Francisco, New YorkOur teams work on some of the firm's highest priority strategic initiatives, including large-scale generative AI systems, intelligent agents, predictive analytics, optimization engines, operational risk solutions, and AI platforms that accelerate innovation across BlackRock. Solutions developed often use multiple subject areas, including Generative AI, machine learning, and optimization, and combine original methods with pioneering solutions available in industry and academia.
Lead Software Engineer, Model Serving Platform SciforiumLead Software Engineer, Model Serving PlatformSan Francisco, CaliforniaBacked by multi-million-dollar funding and direct sponsorship from AMD with hands-on support from AMD engineers the team is scaling rapidly to build the full stack powering frontier AI models and real-time applications. Experience with ML systems engineering, distributed GPU scheduling, open source inference engine like vLLM, Sglang, or TRT-LLM.
Machine Learning Infrastructure Engineer, Model Inference AbridgeMachine Learning Infrastructure Engineer, Model InferenceSan Francisco, CAAs an ML Infrastructure Engineer, Model Inference at Abridge, you'll play a pivotal role in building and optimizing the core inference infrastructure that powers our machine learning models. Powered by Linked Evidence and our purpose-built, auditable AI, we are the only company that maps AI-generated summaries to ground truth, helping providers quickly trust and verify the output.
NewML Infra Engineer, Modeling Physical IntelligenceML Infra Engineer, ModelingSan Francisco, CaliforniaThe ML Infrastructure team supports and accelerates PI’s core modeling efforts by building the systems that make large-scale training reliable, reproducible, and fast. Own training/inference infrastructure: Design, implement, and maintain systems for large-scale model training, including scheduling, job management, checkpointing, and metrics/logging.
Software Engineer, Models MeterSoftware Engineer, ModelsSan Francisco, CaliforniaIn addition to your customers, network engineers, you’ll partner closely with two research engineers who have deep ML backgrounds and a clear picture of what training data needs to look like. When a network engineer looks at a set of device stats and figures out it’s upstream packet loss — not a hardware failure, not a misconfiguration, specifically upstream packet loss — that reasoning lives in their head.
Full Stack Engineer, Scientific AI Models BenchlingFull Stack Engineer, Scientific AI ModelsSan Francisco, CAAlphaFold or Boltz2) predict structures, predict scientific properties, and generate new drug designs, acting as a design partner and a major time saver to scientists who are creating life-saving therapeutics. Projects you might work on include: adding new models as soon as they're published, improving model performance and scalability, and enabling scientists to automate their in-silico workflows by chaining models together into pipelines.
Senior / Principal ML Scientist, Foundation Models for Life Sciences Lila SciencesSenior / Principal ML Scientist, Foundation Models for Life SciencesSan Francisco, California$268,000–$384,000 / yearYou will shape the technical direction for how ML models are trained, evaluated, and deployed at scale, collaborate closely with AI scientists and experimental researchers to close the computational–experimental loop, and drive Lila's ML infrastructure toward the next generation of capabilities. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.