Location Bay Area Preferred

Description

Head of GTM, Physical AI

Bagel Labs is an AI research lab and infrastructure company building distributed training systems for diffusion-heavy physical AI. Our work started with the Paris family of image and video models and now extends toward physical-AI workloads where world models, action representations, simulation, and heterogeneous compute become first-order bottlenecks.

We ignore years of experience and pedigree. If you have high agency, strong technical taste, and can create momentum in ambiguous markets, we want to hear from you. Every requirement below is flexible for a candidate with enough judgment and network density.

Role Overview

You will own Bagel Labs' physical-AI go-to-market motion. The job is to turn Bagel Labs' distributed-training advantage into a real market wedge with teams building robotics, autonomy, simulation, embodied AI, industrial AI, world-model, and diffusion-heavy physical-AI model stacks.

Key Responsibilities

• Define and prioritize Bagel Labs' physical-AI ICP across robotics, autonomy, simulation, industrial AI, embodied AI, video/world-model, and model-stack teams.
• Build a focused GTM pipeline and move the best accounts from first conversation to written technical evaluation, design partnership, or paid pilot.
• Lead technical-commercial conversations with founders, ML leads, infra owners, research leads, and executives.
• Translate Bagel Labs' DDM architecture into clear buyer language around training economics, heterogeneous compute, specialization, and model-stack constraints.
• Package buyer requirements back into research and engineering priorities for the physical-AI proof motion.
• Build the early GTM operating system: account maps, qualification criteria, evaluation artifacts, deal notes, and learning loops.

Who You Might Be

You know how technical markets actually open. You can find the right physical-AI teams, explain why Bagel Labs matters to them, and earn enough trust to get their real workload constraints on the table.

You might be an ex-founder, first business hire, founding GTM lead, technical BD lead, infrastructure GTM operator, or product-minded commercial lead from robotics, simulation, AI infrastructure, autonomy, developer platforms, GPU/cloud, or deep-tech markets.

Desired Skills

• Experience owning early GTM, business development, technical sales, ecosystem, or design-partner motion in a hard technical market.
• Technical credibility with AI infrastructure, robotics, simulation, autonomy, model-platform, generative-model, or GPU/cloud buyers.
• Strong written and verbal communication in technical-commercial settings.
• Bias to action, high agency, and independent judgment.

What We Offer

• Direct access to the CEO and core research team.
• Competitive cash plus meaningful equity.
• A chance to define the first GTM wedge for Bagel Labs' physical-AI infrastructure thesis.
• A front-row seat to one of the hardest infrastructure problems in generative AI.

Apply

Apply via the Bagel Labs careers page.

Required:

• Name
• Email
• X or LinkedIn profile

Optional:

• Resume (PDF, DOC, or DOCX — max 10 MB)

Please click on the link for full job description

What You'll Do

• Build and validate AI-driven VFX workflows: Design end-to-end pipelines that integrate Firefly Foundry's custom-trained diffusion and video models into compositing, look-dev, previs, and virtual production. You'll write working prototypes, not slide decks to prove out new approaches with real shot data.
• Solve hard production problems: Tackle the issues that block adoption: temporal coherence across shot sequences, maintaining art-directable control over generated elements, matching on-set lighting and lens characteristics, and hitting the fidelity bar that supervisors demand.
• Own the integration surface: Define how Firefly Foundry models plug into Nuke, Houdini, Maya, After Effects, Premiere Pro, and Substance 3D. Design the APIs, node graphs, and plugin architectures that make AI-generated assets first-class citizens in existing pipelines, including USD/OpenEXR/ACES-compliant outputs.
• Shape the product from the production floor: Translate what you learn from studio engagements into concrete product requirements for the Firefly and Firefly Foundry engineering teams.
• Implement and prototype multi-modal model orchestration: Design the orchestration layer across image, video, animation, and 3D generation models — maintaining character identity, texture consistency, and style transfer constraints across all modalities.
• Engage studio and VFX leadership: Present to CTOs, VFX supervisors, and heads of production. Run technical deep-dives and creative workshops.
• Codify repeatable playbooks: Document reference architectures, prompt engineering strategies for VFX use cases, quality evaluation pipelines, and deployment patterns.

Required

• 5–10+ years in VFX engineering, pipeline TD, or tools development with shipped credits in film, episodic, or AAA gaming.
• Deep fluency in production VFX workflows: compositing (Nuke), 3D (Maya/Houdini), rendering, look-dev, previs/postvis, editorial handoff, and review (Shotgrid, Frame.io, or equivalent).
• Working knowledge of generative AI fundamentals e.g. diffusion models, LoRA/fine-tuning, ControlNet-style conditioning, prompt engineering, and evaluation metrics (FID, CLIP, perceptual loss).
• Proficiency in Python and at least one of C++, Rust, or TypeScript. Comfortable writing production-quality code, not just scripts.
• Familiarity with VFX data standards: OpenEXR, ACES, USD, Alembic, OpenColorIO.
• Ability to communicate technical concepts to non-technical studio leadership. Strong written communication, you can write a clear 1-pager or technical design doc.

Preferred

• Credits on major feature films or high-profile episodic VFX (think tentpole-scale, not just indie shorts).
• Experience with real-time rendering (Unreal Engine, virtual production stages, LED volumes).
• Hands-on experience fine-tuning or deploying generative models (Stable Diffusion, Runway, ComfyUI, or similar).
• Background in computer vision or image processing (optical flow, segmentation, depth estimation, upscaling).
• Prior experience in a customer-facing technical role (solutions engineer, field CTO, technical account lead).

Founding Machine Learning - Eval Layer

We're building the evaluation layer to understand policy failure modes before they hit production. You'll own modeling work that makes the eval trustworthy.

What You'll Do

• Train evaluation models: Develop VLMs that classify and verify policy behavior.
• Build confidence layers: Convert model outputs into trustworthy signals the customer can act on.
• Improve model grounding: Make the eval models reason accurately about physical and spatial scenes.
• Build a self-improving eval layer: Develop data engine that makes the eval models sharper with each customer's deployments and corrections.

Requirements

• Very strong coding in Python and PyTorch.
• VLM/LLM training: Track record in training VLMs or LLMs.
• Evals experience: Developed and shipped evals for VLMs or LLMs.

Role Details

Job type: Full-time
Experience: Any, new grads ok
Location: San Francisco, CA, US
Remote: No
US visas: Will sponsor
Equity: 0.50% - 2.00%
Salary: $150K - $275K
Hiring manager: Hemanth Sarabu

About One Robot

One Robot builds task-specific world models and an evaluation platform for robot manipulation policies.

Training end-to-end policies for robots is vibes-based today. Teams collect data, train, deploy on a real robot, find out what fails, collect more, retry. We replace the trial-and-error with rigorous validation that tells you where your policy will fail and what data to collect to fix it.

Robotics can't industrialize without an evaluation layer. We're building it.

We're solving challenging technical problems around long-horizon autoregressive generation, world model controllability, and closing the sim-to-real gap. We work with real customer data, real failures, and real deployment pressure.

We're based in San Francisco, backed by Accel, YC, several exited founders, and engineering leaders at leading AI companies.

We're small and deliberately so. Everyone is an IC with deep ownership of a wide surface area. The culture is fast iteration and direct responsibility.

Hemanth Sarabu and Elton Shon co-founded One Robot after leading robot learning together at Industrial Next (YC W22), bringing experience from Google, NASA JPL, and Tesla.

USA, California, Santa Clara

We are now looking for a Senior Research Scientist for Generative AI!

NVIDIA is searching for a world-class researcher in generative AI to join our research team. You will be conducting original research for generative AI applications, including image generation, video generation, 3D generation, and audio generation. You will be working with a team of world-class researchers eager to make great impacts with generative AI models. You will be building research prototypes and scaling them with large datasets and compute. After building prototypes that demonstrate the promise of your research, you will work with product teams to help them integrate your ideas into products.

What you'll be doing: - Conduct original research in the space of generative AI - Implement and train large-scale generative AI models for various content creation applications - Collaborate with other research team members, a diverse set of internal product teams, and external researchers - Have a broader impact through the transfer of the technology you've developed to relevant product groups

What we need to see: - Ph.D. in Computer Science/Engineering, Electrical Engineering, or a related field (or equivalent experience). - 5+ years of relevant research experience. - Excellent collaboration and interpersonal skills - Excellent python/C++ programming skills - Great knowledge of common deep-learning frameworks - Experience in processing or curating large-scale datasets - Excellent knowledge of theory and practice of deep learning, computer vision, natural language processing, or computer graphics - Track record of research excellence or significant product development

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous research scientist with a genuine passion for advancing the state of AI? If so, we want to hear from you!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 192,000 USD - 304,750 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Location: Beijing

Responsibilities 1. Foundation Models ①Build a unified foundation model for autonomous driving; develop multimodal backbone architectures and sub‑tasks; apply model distillation and lightweighting. ②Leverage language alignment, generative self‑supervision, semi‑supervision, and other techniques to advance large‑scale pre‑training, improving generalization and robustness in complex scenarios. 2. Data & Model Iteration ①Build automated data pipelines using 3D geometry, reconstruction, and related technologies. ②Design and implement a multi‑stage pre‑training to post‑training workflow, along with data utilization strategies.

Requirements 1. Full‑time Master’s degree or above in Computer Science, Electronic Engineering, Automation, Vehicle Engineering, or a related field, with research focused on computer vision, deep learning, robotics, or equivalent areas. 2. Familiar with mainstream deep learning frameworks; proficient in the end‑to‑end workflow of model training, fine‑tuning, and deployment. 3. Experience in developing foundation models (e.g., Transformer, multimodal fusion models); familiar with distributed training, mixed‑precision acceleration, and related techniques. 4. Solid programming skills with strong proficiency in Python/C++; ability to perform high‑performance code optimization and develop complex systems. 5. Strong passion for autonomous driving technology, with excellent learning ability and technical insight. 6. First‑author publications in top‑tier conferences or journals (e.g., CVPR, ICCV, ECCV, NeurIPS, ICML) is a strong plus. 7. Hands‑on experience in autonomous driving, robotics, or large‑scale AI model projects is preferred. 8. Familiarity with large‑scale data processing tools; experience in large‑scale distributed model training (1,000+ cards/nodes) is highly preferred.

Foster City, CA

Do you enjoy applying machine learning to complex, real-world problems in autonomous vehicle testing? The Simulation Scenario Generation team is looking for a ML Engineer to enable next-generation scalable AV scenario creation workflows. This ranges from generating large-scale traffic simulations to extending our agentic AI system to assist in synthetic scenario creation from a natural language test specification. This role offers a unique chance to deliver immediate user impact while contributing to long-term AI-driven safety validation. In this role, you will: Contribute to tooling for AI-based scenario understanding and validation. Synthesize realistic AV simulation scenarios with dynamic (e.g., traffic) and static features. Integrate and validate LLMs/VLMs and implement other models for complex scenario generation workflows, leveraging techniques like agentic tool use. Collaborate directly with internal customers and partner teams to provide generative AI solutions for their test creation workflows. Directly contribute to the safety and reliability of Zoox's autonomous software. Qualifications MS or PhD in Computer Science, Machine Learning, or related field 5+ years of industry experience in Machine Learning Proficiency in Python and ML libraries (PyTorch, JAX, NumPy, etc.) demonstrated through professional or research projects Demonstrated experience in transformer and diffusion architectures Practical experience in dataset creation for fine-tuning, system integration of ML models into production, or optimization techniques for low-latency inference systems Bonus Qualifications Familiarity with autonomous vehicles, robotics, and/or complex simulation environments Hands-on experience in areas like program synthesis and/or formal methods/V&V Relevant publications in conferences (e.g., CVPR, ICCV, RSS, and/or ICRA) $233,000 - $290,000 a year Base Salary Range

Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video subscriptions such as Apple TV+, HBO Max, Peacock, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads.

Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience.

As a Prime Video team member, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people.

We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you!

Key job responsibilities As a highly experienced and seasoned science leader, you will apply state of the art natural language processing and computer vision research to video centric digital media, while also responsible for creating and maintaining the best environment for applied science in order to recruit, retain and develop top talent. You will lead the research direction for a team of deeply talented applied scientists, creating the roadmaps for forward-looking research and communicate them effectively to senior leadership. You will also hire and develop applied scientists - growing the team to meet the evolving needs of our customers.

About the team This team's mission is to deeply understand all content and empower all customers with relevant language options, innovative accessibility assists, and rich title-information across all their content-experiences on Prime Video. We create and publish content on-time that's meaningful, accurate, and accessible to every customer globally. We delight our customers by pushing the boundaries of content understanding and enrichment. Through inclusion and innovation, we do the most fulfilling work of our career.

Locations: Toronto, ON / Pittsburgh, PA / San Francisco, CA

You will...

• Be part of a team of multidisciplinary Research Scientists and Engineers using an AI-first approach to enable safe self-driving at scale.
• Lead or Contribute to an AI research project, pushing the frontiers of the field by developing new algorithms for Autonomous Vehicle (AV). This includes topics such as perception, prediction, motion planning, controls, simulation, mapping, localization, core AI, etc.
• Design, implement, train, and optimize novel algorithms on self-driving vehicles and various production systems.
• Be encouraged to submit and publish work externally at top machine learning, computer vision, and robotics conferences (NeurIPS, ICLR, ICML, CVPR, etc.), post to our company blog.

Qualifications:

• Pursuing PhD degree in Computer Science, Engineering, AI, Machine Learning, Computer Vision, Robotics and/or similar technical field(s) of study.
• Demonstrated research/software engineering experience: through previous internships, work experience, coding competitions, and/or research projects and papers.
• At least one publication in top Machine Learning, Computer Vision, or Robotics conferences.
• Strong quantitative background and coursework in or working knowledge of linear algebra, calculus, and probability.
• Proficient in reading and coding in Python and/or C++..
• Open-minded and collaborative team player with willingness to help others.
• Passionate about self-driving technologies, solving hard problems, and creating innovative solutions.

Application Instructions:

• To be considered for an internship/co-op, please add your most up to date academic transcripts alongside with your resume for further review.

The US hourly range for this role is: $60 USD and the Canada hourly range for this role is: $60-$65 CAD in addition to competitive perks & benefits. Waabi US Inc. and Waabi Canada Inc.'s yearly salary ranges are determined based on several factors in accordance with the Company’s compensation practices. The salary base range is reflective of the minimum and maximum target for new hire salaries for the position across all US and Canada locations.

VinUniversity (VinUni) is Vietnam’s first private, not-for-profit university established to international standards, aiming to become a world-class institution. It integrates global university models with Vietnam’s cultural and economic context and collaborates with Cornell University and University of Pennsylvania. The university includes four colleges: Arts and Sciences, Business and Management, Engineering and Computer Science, and Health Sciences.

VinUni is founded by Vingroup, a major private corporation in Asia operating in technology, real estate, infrastructure, green energy, and social enterprises. It connects with companies such as VinFast, Vinpearl, Vinmec, Vinschool, and Vinhomes.

In September 2024, VinUni became the youngest and fastest university globally to achieve QS 5 Stars in nine categories. In October 2024, it was appointed by UNESCO as the first University Chair focusing on Environmental Leadership, Cultural Heritage, and Biodiversity.

VinUni is building a strong innovation ecosystem through research centers and focuses on AI, Data Science, Environmental Intelligence, Health Sciences, Policy Development, and Sustainable Societies.

The Faculty of Environmental Science and Engineering position at CECS is research-focused and works with the Smart Green Transformation Center (GREEN-X). Faculty members lead pilot treatment system design and validation, develop scalable and deployable environmental solutions, and quantify pollutant reduction. They also support emission factor development, aquaculture impact assessments, MRV standards, and environmental indicators for LCA-based frameworks.

Preferred expertise includes Environmental Monitoring and Assessment, Pollution Control and Remediation, Waste Valorization and Resource Recovery, and Life Cycle Assessment (LCA) and Emission Factor Analysis.

CECS provides interdisciplinary education and research through seven centers and strong industry collaboration within the Vingroup ecosystem. GREEN-X focuses on smart green transformation, including carbon tracking, smart aquaculture, circular economy, green policy, and innovation competitiveness. Its key projects include CarbonFootPrint, SmartMarine, SmartWaste, GreenPolicy, and VIGGI.

Faculty responsibilities include research, teaching, and service. Research involves high-impact publications, funding acquisition, interdisciplinary collaboration, and commercialization. Teaching includes curriculum development, lectures, assessment, and student supervision. Service includes committees, recruitment, accreditation, and strategic initiatives.

Applicants must hold a PhD in IoT, robotics, autonomous systems, or related fields, with strong research, teaching, and industry engagement experience.

Assistant Professors should have postdoctoral experience and research potential. Associate Professors require strong teaching records and at least five years of funded research leadership. Professors require at least ten years of internationally recognized research leadership, major publications, awards, and mentorship excellence.

Location: Palo Alto, CA

About Metamorphic

Metamorphic is developing new approaches to intelligence by combining machine learning with large-scale experimental neuroscience, informed by the principles that make the brain efficient, flexible, and robust. We are building foundation models trained on rich, continuous neural data — a high-resolution model of the brain at a scale never before possible.

Our founding team spans machine learning, neuroscience, and neurotechnology, with prior work including the MICrONS project, Neuropixels, and the Enigma project, as well as foundational scientific contributions in AI, neural computation, and embodied intelligence. Our work sits at the frontier of AI research, and we believe the highest-impact discoveries will come from researchers and engineers working as a single, tightly collaborative team.

The name Metamorphic reflects our belief that the next advances in intelligence will come from a change in form, beyond scale — from artificial to natural intelligence.

About the Role

We are hiring a Research Scientist to advance the learning algorithms and models that drive our neuro-aligned embodied agents. You will design, train, and evaluate the methods that connect our foundation models to physical systems, working across areas such as world models, action models, reinforcement learning, and learning from demonstration. A central part of your work will be exploring how principles drawn from our neuroscience research can shape better representations, dynamics, and behaviors in embodied agents.

Unlike most labs working in this space, Metamorphic approaches embodied intelligence from the joint perspective of machine learning and large-scale neuroscience. This interdisciplinary research paradigm unlocks a new path towards safe AGI, and you will have substantial input into it. You will own end-to-end significant pieces of the research agenda from problem formulation through experimentation, scaling, and evaluation in both simulation and the real world. You will work closely with researchers and engineers across the team, with substantial autonomy over how methods and infrastructure evolve as the work scales.

You'll thrive in this role if you:

• Are excited about working in a fast-paced, production-focused research lab that often requires moving between algorithmic research, large-scale experimentation, and hands-on work in the same week
• Have strong research taste and engineering instincts, and can move quickly between writing, shipping experiments, and rigorous evaluation
• Are comfortable owning a research direction end-to-end — formulating the problem, designing experiments, running them at scale, and interpreting results carefully
• Enjoy pair programming and deeply collaborative work, including hands-on time with researchers and engineers across disciplines
• Are eager to engage seriously with neuroscience and to let biological principles shape the algorithms you build, rather than treating them as decoration
• Are enthusiastic to work at an organization that functions as a single, cohesive team pursuing large-scale AI research
• Have ambitious goals for AI progress and are excited to create the best outcomes over the long term

We offer:

• The chance to work on one of the most scientifically consequential AI projects being pursued today
• A small, world-class team where your contributions directly shape the science and the company
• Competitive compensation and benefits, along with visa sponsorship
• Strong mentorship and career development

More details

Visit our job posting to learn more about the role.