ZipRecruiter

Log In

1

Nerf Machine Learning Jobs (NOW HIRING)

Nvidia

Neural Graphics Engineer

Santa Clara, CA

$164K - $203K/yr

... machine learning, or computer vision * A drive to learn, grow, and take on challenging problems Ways to Stand Out from the Crowd: * Hands-on experience with neural rendering (NeRF, Gaussian splatting ...

next page

Showing results 1-20

All JobsNerf Machine Learning Jobs

Nerf Machine Learning information

What is the difference between Nerf Machine Learning vs Computer Vision Engineer?

AspectNerf Machine LearningComputer Vision Engineer
Required CredentialsDegree in Computer Science, Data Science, or related fields; experience with machine learning frameworksDegree in Computer Science, Electrical Engineering, or related fields; experience with image processing and vision algorithms
Work EnvironmentResearch labs, AI startups, tech companies focusing on neural rendering and 3D modelingTech companies, research institutions, industries involving image analysis and autonomous systems
Industry UsagePrimarily in AI research, neural rendering, 3D scene reconstructionIn autonomous vehicles, robotics, healthcare imaging, and security systems

While both roles involve advanced AI techniques, Nerf Machine Learning focuses on neural radiance fields and 3D scene understanding, whereas Computer Vision Engineers specialize in analyzing and interpreting visual data from images and videos. The roles often overlap in AI research but serve different application areas within the tech industry.

Is ML a high paying job?

Machine Learning (ML) jobs, including roles like ML engineer or data scientist, are generally considered high paying within the tech industry due to the specialized skills required, such as programming, statistics, and knowledge of ML frameworks. Salaries vary based on experience, location, and company size, but they tend to be above average compared to many other professions in technology.

How does a Nerf Machine Learning Engineer typically collaborate with 3D artists and graphics engineers in a project?

As a Nerf Machine Learning Engineer, you’ll frequently work alongside 3D artists and graphics engineers to integrate neural radiance field (NeRF) models into real-time rendering pipelines. Collaboration often involves translating real-world scene data processed by NeRF into formats that can be manipulated by artists, as well as optimizing model performance for interactive applications. Regular meetings and iterative feedback ensure that visual quality and technical requirements align, making strong communication and flexibility essential for success in this role.

What are the key skills and qualifications needed to thrive as a NeRF (Neural Radiance Fields) Machine Learning Engineer, and why are they important?

To thrive as a NeRF Machine Learning Engineer, you need a strong background in computer vision, deep learning, and mathematics, typically supported by a degree in computer science or a related field. Proficiency with Python, PyTorch or TensorFlow, 3D graphics libraries, and familiarity with NeRF-specific frameworks is essential. Strong problem-solving skills, creativity, and effective communication set standout engineers apart in this field. These skills enable the development of advanced 3D scene reconstruction models and ensure efficient collaboration within multidisciplinary teams.

What are Nerf Machine Learning jobs?

Nerf Machine Learning jobs involve working with Neural Radiance Fields (NeRF), a type of machine learning model used for 3D scene reconstruction from 2D images. Professionals in this field develop, train, and optimize NeRF algorithms to create realistic 3D representations for applications in computer vision, graphics, virtual reality, and robotics. These roles typically require strong backgrounds in deep learning, computer vision, and software engineering, along with experience in frameworks like PyTorch or TensorFlow.

Will MLE be replaced by AI?

In the context of Nerf Machine Learning roles, machine learning engineers (MLEs) focus on developing and deploying models, which AI systems can automate or enhance. While AI tools can assist MLEs in tasks like data preprocessing and model tuning, human expertise remains essential for designing, interpreting, and maintaining complex models. Therefore, AI is more likely to augment rather than fully replace MLEs in the foreseeable future.

What jobs can I get with AI ML?

With AI and ML skills, you can pursue roles such as Machine Learning Engineer, Data Scientist, AI Research Scientist, or AI Software Developer. These jobs typically require knowledge of programming languages like Python, experience with machine learning frameworks, and understanding of algorithms and data analysis. They are common in technology companies, research institutions, and industries adopting AI solutions.

What is nerf deep learning?

Nerf deep learning refers to the application of neural network models to Neural Radiance Fields (NeRF), a technique used to generate 3D scenes from 2D images. In a machine learning context, it involves training models to synthesize realistic 3D representations, often requiring skills in computer vision, 3D modeling, and deep learning frameworks like TensorFlow or PyTorch.
More about Nerf Machine Learning jobs
What cities are hiring for Nerf Machine Learning jobs? Cities with the most Nerf Machine Learning job openings:
What states have the most Nerf Machine Learning jobs? States with the most job openings for Nerf Machine Learning jobs include:
What job categories do people searching Nerf Machine Learning jobs look for? The top searched job categories for Nerf Machine Learning jobs are:
Nerf Machine Learning jobs near you

Research Scientist- Vision-Language-Action (VLA) Models

Bosch Group

Sunnyvale, CA • On-site

Full-time

Medical, Life, Retirement, PTO

Re-posted 17 days ago

Job description

Company Description
The Bosch Research and Technology Center North America with offices in Sunnyvale, California, Pittsburgh, Pennsylvania, and Cambridge, Massachusetts is a part of the global Bosch Group (www.bosch.com), a company with over 70 billion euro revenue, 400,000 employees worldwide, a very diverse product portfolio, and a history spanning over 125 years. The Research and Technology Center North America (RTC-NA) is dedicated to providing technologies and system solutions for various Bosch business fields, primarily in the field of artificial intelligence, energy technologies, internet technologies, circuit design, semiconductors and wireless, as well as advanced MEMS design.
As a part of the global research, our AI research in Silicon Valley focuses on Foundation Models, Big Data Visual Analytics, Explainable AI (XAI), Natural Language Processing, Computer Vision & Mixed Reality, Cloud Robotics, Data Science, AI System Engineering, Time-series Analysis. We develop scalable, intelligent, and trustworthy AIoT solutions for Bosch products and services in application areas such as automated driving, advanced driver assistance systems (ADAS), robotics, smart manufacturing, enterprise AI, health care, smart home and building solutions.
Originating from the AI research in Silicon Valley, our Intelligent Autonomous Systems group is responsible for enabling future autonomous Bosch products by pushing the boundaries of automated driving, advanced driver assistance systems (ADAS), robotics and automation through key innovations that encompass system architecture and AI components. These include methods for motion planning, high level task planning and decision making as well as systems for making these technologies work on real products by building frameworks that take advantage of technologies in the field of reliable distributed computing. We work with internal partners of different Bosch business units to transfer our solutions into future products. We also actively collaborate with leading groups in academia and industry to promote research ideas and publish research findings in internationally renowned conferences and journals such as CVPR, ICRA, IROS, RSS, NeurIPS and CoRL.
Job Description
As a Research Scientist- Vision-Language-Action (VLA) Models, you contribute to research projects at the forefront of the ADAS/AD industry. Key responsibilities include:
  • Conduct research and engineering in core AI and machine learning fields to enable Embodied AI (including computer vision, autonomous planning, open-world learning, and so on) for related business domains of ADAS/AD, industrial automation, robotics etc.
  • Push the boundaries in (modular) end-to-end perception and planning for ADAS/AD, incorporating advancements in large vision-language-(action) models to aid reasoning capabilities and explainability.
  • Collaborate cross-functionally with global research and engineering teams to ensure seamless technology transfer and system integration.
  • Implement research results to solve real-world challenges, ensuring high-quality system integration within Bosch's existing platforms.
  • Stay at the forefront of innovation by actively engaging with academic and industry communities through conferences, workshops, and technical events.
  • Document and disseminate research findings through high-caliber publications and/or patent submissions.

Qualifications
Basic Qualifications
  • Ph.D. in Computer Science, Robotics or a related discipline or Master's degree with >= 2 years industry experience after graduation.
  • A minimum of 3 years of R&D experience, or an equivalent graduate research background, primarily in AI technologies including Computer Vision and Robotic or Automotive Motion and Behavioral Planning.
  • Proficiency in one or more programming languages commonly used in machine learning (e.g., Python, C++, Rust).
  • Strong interpersonal, communication, and teamwork capabilities.
  • Knowledge of major machine learning frameworks like TensorFlow or PyTorch.
  • Hands-on experience in reinforcement learning for behavior or motion planning or other applicable contexts and familiarity with common RL techniques (e.g. PPO, DQN, DDPG).
  • A strong portfolio of publications in premier machine learning, deep learning, robotics and computer vision journals and conferences.

Preferred Qualifications
  • Experience with real-world product development and deployment of autonomous systems.
  • Hands-on experience building and applying multimodal transformer-based sequence-to-sequence models, especially multimodal vision-language-action models.
  • Hands-on experience in computer vision and deep learning, with work in any of the following areas: multimodal transformers, multimodal language models, diffusion models, NeRF, gaussian splatting, object detection / segmentation, 3D scene understanding, sensor calibration, SfM, voxel/BEV grid-based feature representation.

Additional Information
We offer a competitive base salary for this position with a range in US-California of --$165,000 - $185,000 along with an annual corporate bonus, and a long-term incentive bonus designed to reward sustained impact and contribution over time. Within the salary range, the individual pay is determined based on several factors, including, but not limited to, work experience and job knowledge, complexity of the role, job location, etc.
Your well-being matters at Bosch! We offer a a benefits package designed to empower you in every area of your life. This includes premium health coverage, a 401(k) with generous matching, resources for financial planning and goal setting, ample paid time off, parental leave, and comprehensive life and disability protection. Your Recruiter can share more details for this position during the interview process.
Learn more about our full benefits offerings by visiting: https://www.myboschbenefits.com/public/welcome.
Equal Opportunity Employer, including disability / veterans.
*Bosch adheres to Federal, State, and Local laws regarding drug-testing. Employment is contingent upon the successful completion of a drug screen and background check. Candidates who have been offered the position must pass both screenings before their start date.
#LI-JM1

Apply