Machine Learning Infrastructure Engineer David Joseph & CompanyMachine Learning Infrastructure EngineerSan Francisco, California$200,000–$400,000 / yearTech stack: Distributed training frameworks (FSDP, DeepSpeed), NVIDIA GPUs, Linux, Python, C++, Kubernetes/Docker, and a major cloud platform (GCP, AWS, or Azure). Research and test training approaches, including parallelization techniques and numerical-precision trade-offs across model scales.
Senior Machine Learning Engineer - Perception Bonsai RoboticsSenior Machine Learning Engineer - PerceptionSan Jose, CaliforniaStrong background in most of the following technologies: ML modeling (preferably object detection & segmentation), classical CV algorithms and multiview geometry. You should have a strong background in any of the following technologies: ML modeling (preferably object detection & segmentation), classical CV algorithms and multi-view geometry.
Machine Learning Scientist - Natural Language Processing (NLP) - Vice President - Machine Learning Center of Excellence JPMorgan Chase & CoMachine Learning Scientist - Natural Language Processing (NLP) - Vice President - Machine Learning Center of ExcellencePalo Alto, CAThe CDAO is also responsible for developing and implementing solutions that support the firm's commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
Founding Machine Learning Engineer Recruiting From ScratchFounding Machine Learning EngineerSan Francisco, CaliforniaThis role is ideal for ML engineers who want to operate at the frontier of applied NLP and retrieval—owning core intelligence systems that power how AI agents interact with real-world data at scale. Instead of traditional search workflows designed for humans, the platform provides APIs that allow AI systems to retrieve high-fidelity, structured data directly from source systems.
EMIR Engineer, Annapurna Labs - Cloud Scale Machine Learning Amazon.com IncEMIR Engineer, Annapurna Labs - Cloud Scale Machine LearningCupertino, CAIn this role, you'll be working directly with architects, designers, verification engineers, power integrity engineers and physical design experts - defining best practices in power grid design, developing test cases & vectors to model demand currents accurately, modeling & signing-off EMIR taking into account board and package impact, advancing the state-of-the-art in EMIR analysis and modeling. We encourage collaboration and teamwork with multiple teams and engineers including architects, RTL designers, Verification engineers,, Physical Design engineers, Emulation engineers and software engineers.
Machine Learning Digital Design Engineer Meta Platforms IncMachine Learning Digital Design EngineerSunnyvale, CAContribute to ASIC digital µArchitecture and design Assist performance/power analysis of the design and help meet power and performance targets Work with architects to map algorithms onto the hardware and specify requirements for IP and subsystems integration Collaborate with adjacent teams such as Verification, Physical Design, and Design-for-Test Develop micro-architecture, RTL coding, and design verification for complex IPs Drive IP/sub-system micro-architecture and RTL design in collaboration with DV and PD leadsBachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 6+ years of experience as a Hardware Design Engineer for production silicon shipped in volume Experience in digital design µArchitecture, RTL coding, and micro-architecture development Experience communicating technical design decisions and trade-offs to cross-functional partners such as verification, physical design, and architecture teams Experience in ML accelerator subsystems and top level design Experience in SoC integration and ASIC architecture Knowledge of microcontrollers, DSP, CDC and power sequence Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologiesMeta builds technologies that help people connect, find communities, and grow businesses. You will collaborate with researchers and engineers to design, implement, and optimize low-power hardware accelerators, state-of-the-art SoCs, and custom silicon solutions that enable the next generation of innovative devices and hardware.
Senior Virtual Platform Software Engineer, Annapurna Labs Machine Learning Accelerators, AWS Amazon.com IncSenior Virtual Platform Software Engineer, Annapurna Labs Machine Learning Accelerators, AWSCupertino, CAOur team builds virtual platforms - full-system C++ and SystemC models of these custom SoCs - that let software teams start development months before silicon arrives. What youll do: Build and own functional models of SoC subsystems that integrate into our full-system virtual platform, used by firmware, driver, runtime, and application software teams.
Virtual Platform Software Engineer, Annapurna Labs Machine Learning Accelerators, AWS Amazon.com IncVirtual Platform Software Engineer, Annapurna Labs Machine Learning Accelerators, AWSCupertino, CAWhat youll do: - Build and own functional models of SoC subsystems that integrate into our full-system virtual platform, used by firmware, driver, runtime, and application software teams - Design models for usability and performance - your customers are software engineers who need to run real workloads on your platform efficiently - Develop and improve the virtual platform infrastructure: QEMU integration, simulation performance, build and release tooling, and customer-facing documentation - Work with software teams (your primary customers) to understand their workflows, debug issues on the platform, and shape the model to maximize their productivity - Drive simulation performance improvements so the platform can handle increasingly complex workloads at scale - Contribute to model architecture decisions - choosing the right level of abstraction and fidelity for each subsystem based on customer needs Why this role is interesting: - Youll own a product that software teams across AWS depend on - they literally cant start development without your virtual platform - The engineering challenges are genuinely interesting: full-system simulation, multi-subsystem integration, QEMU development, performance optimization at scale - Youll see the direct impact of your work when software teams hit the ground running on new silicon - As the team grows, theres a path into architectural modeling - using the platform to explore design alternatives and influence chip architecture - Small team, startup pace, big impact inside AWSs custom silicon org You will thrive in this role if you: - Have built functional models, virtual platforms, or system-level simulations for SoCs, ASICs, GPUs, or CPUs - Think of yourself as a software engineer first, with deep domain knowledge in chip architecture - Are comfortable in C++ or SystemC, and familiar with Python for tooling - Care about your customers experience - you think about usability, documentation, and reliability, not just model accuracy - Are interested in expanding into performance or architectural modeling as the team scales - Enjoy working on a small, high-impact team where you own significant pieces of the stack No ML background needed. Our team builds virtual platforms - full-system C++ and SystemC models of these custom SoCs - that let software teams start development months before silicon arrives.
Machine Learning Researcher, Multimodal LLMs BlandMachine Learning Researcher, Multimodal LLMsSan Francisco, California$180,000–$260,000 / yearVoice is quickly becoming the primary interface between businesses and their customers, and we are building the models and infrastructure that make those interactions feel natural, reliable, and genuinely human. You will define how our agents listen, think, and act in real time , integrating streaming audio, tool execution, and dynamic context into a single coherent system.
NewFounding Machine Learning Engineer Orbit Neuro Co.Founding Machine Learning EngineerSan Francisco, CaliforniaWe’re backed by the founders and execs of the leading companies in AI, neurotech, consumer hardware and pharmaceuticals - including Google, Hugging Face, Apple, Stability, Microsoft and Dropbox. You have: An BS or higher in Computer Science, Electrical Engineering, Applied Mathematics, or a related STEM field (exceptional self-taught researchers also considered).
Senior AI SoC Modeling Engineer, Annapurna Labs Machine Learning Accelerators, AWS Amazon.com IncSenior AI SoC Modeling Engineer, Annapurna Labs Machine Learning Accelerators, AWSCupertino, CAWhat you"ll do: Develop and maintain high-fidelity functional model of AI/ML accelerator and its SoC subsystems, including compute engines, memory hierarchies, on-chip interconnects, and data paths - translating architecture specs and RTL behavior into accurate, testable C++ models. Collaborate with architects/micro-architects, RTL design engineers, ML SW engineers, and compiler engineers to evaluate architecture and microarchitecture tradeoffs and help make hardware design decisions.
Sr. EMIR Engineer, Annapurna Labs - Cloud Scale Machine Learning Amazon.com IncSr. EMIR Engineer, Annapurna Labs - Cloud Scale Machine LearningCupertino, CAIn this role, you'll be working directly with architects, designers, verification engineers, power integrity engineers and physical design experts - defining best practices in power grid design, developing test cases & vectors to model demand currents accurately, modeling & signing-off EMIR taking into account board and package impact, advancing the state-of-the-art in EMIR analysis and modeling. We encourage collaboration and teamwork with multiple teams and engineers including architects, RTL designers, Verification engineers,, Physical Design engineers, Emulation engineers and software engineers.
Staff Machine Learning Engineer Doma Technology LLCStaff Machine Learning EngineerSan Francisco, CA$165,200–$236,300 / yearAn employee's pay position within the base salary range will be based on several factors including, but not limited to, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, shift, travel requirements, sales or revenue-based metrics, any collective bargaining agreements, and business or organizational needs. Doma Technology LLC offers solutions for lenders, real estate professionals, title agents, and homeowners that make closings vastly simpler and more efficient, reducing cost and increasing customer satisfaction.
Senior Machine Learning Engineer - LLM Quantization & Deployment XPENGSenior Machine Learning Engineer - LLM Quantization & DeploymentSanta Clara, CA$174,720–$295,680 / yearDevelop VLA inference models, ensure numerical consistency with training models, and productionize LLM quantization methods, including PTQ, QAT, mixed-precision inference, INT8, FP4, and lower-bit techniques. XPENG is a leading smart technology company at the forefront of innovation, integrating advanced AI and autonomous driving technologies into its vehicles, including electric vehicles (EVs), electric vertical take-off and landing (eVTOL) aircraft, and robotics.
Staff Machine Learning Engineer - LLM Quantization & Deployment XPENGStaff Machine Learning Engineer - LLM Quantization & DeploymentSanta Clara, CA$215,280–$364,320 / yearDevelop VLA inference models, ensure numerical consistency with training models, and productionize LLM quantization methods, including PTQ, QAT, mixed-precision inference, INT8, FP4, and lower-bit techniques. XPENG is a leading smart technology company at the forefront of innovation, integrating advanced AI and autonomous driving technologies into its vehicles, including electric vehicles (EVs), electric vertical take-off and landing (eVTOL) aircraft, and robotics.
NewMachine Learning Intern BlandMachine Learning InternSan Francisco, CaliforniaAs a Research Intern at Bland, you will own a focused research project across our voice stack: speech-to-text, large language models, neural audio codecs, or text-to-speech. Train and evaluate models on large-scale, real-world telephony audio, including the accents, noise, and artifacts that make production speech hard.
AI SoC Modeling Engineer, Annapurna Labs Machine Learning Accelerators, AWS Amazon.com IncAI SoC Modeling Engineer, Annapurna Labs Machine Learning Accelerators, AWSCupertino, CAWhat you"ll do: Develop and maintain high-fidelity functional model of AI/ML accelerator and its SoC subsystems, including compute engines, memory hierarchies, on-chip interconnects, and data paths - translating architecture specs and RTL behavior into accurate, testable C++ models. Collaborate with architects/micro-architects, RTL design engineers, ML SW engineers, and compiler engineers to evaluate architecture and microarchitecture tradeoffs and help make hardware design decisions.
Sr Manager, Machine Learning Engineering AdobeSr Manager, Machine Learning EngineeringSan Jose, California$242,600–$351,225 / yearBy letting customers train private Firefly models on their own intellectual property—under strict data isolation and copyright indemnification—and deploy those models directly into Adobe Creative Cloud, Experience Cloud, and proprietary platforms via Firefly Services APIs, Firefly Foundry closes the gap left by consumer‑grade GenAI tools and empowers brands to deliver ten‑times the creative output at professional quality. Adobe’s industry-leading offerings including Adobe Acrobat Studio, Adobe Express, Adobe Firefly, Creative Cloud, Adobe Experience Platform, Adobe Experience Manager, and GenStudio enable people and businesses to turn ideas into impact, powered by AI and driven by human ingenuity.
Sr. Machine Learning - Compiler Engineer III, AWS Neuron, Annapurna Labs Amazon.com IncSr. Machine Learning - Compiler Engineer III, AWS Neuron, Annapurna LabsCupertino, CAAs you design and code solutions to help our team drive efficiencies in compiler architecture, you'll create compiler optimization and verification passes, build features surface features and peculiarities of AWS accelerators to developers, implement tools to analyze numerical errors, and resolve the root cause of compiler defects. You will be responsible for solving hard compiler optimization problems to achieve optimum performance for variety of ML model families including massive scale large language models like Llama, Deepseek, and beyond as well as stable diffusion, vision transformers and multi-model models.
Machine Learning Data Engineer VizcomMachine Learning Data EngineerSan Francisco, CaliforniaMore than 700,000 designers have worked in Vizcom, and every session leaves a trail: candidates selected, outputs promoted into designs, regions masked and renamed, and entire directions kept or discarded. Researchers as your users: You'll work directly alongside the people using the datasets you build, creating an unusually tight feedback loop between data engineering and research.