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Research Engineer, Manipulation

Scaled Foundations is an AI research and deployment company building general robot intelligence, and we are seeking a Research Engineer to join our team. We conduct focused research and engineering to build generalized robotics foundation models that work across form factors such as aerial, ground, manipulation, and others. We are looking for strong candidates who have a background in robotics and machine learning, with experience in areas like multimodal machine learning; synthetic data generation through simulation; LLMs; reinforcement learning and imitation learning for robotics; efficient training and inference. 

Research Engineer Responsibilities

  • Design methods, tools, and infrastructure to push forward the state-of-the-art in robotic manipulation and foundation models. 

  • Define research goals informed by practical engineering concerns.

  • Adapt standard machine learning models and frameworks to manipulation applications.

  • Work with high-fidelity simulation platforms for synthetic data generation.

  • Develop sim2real and teleoperation pipelines for manipulation tasks.

  • Design data loading and training pipelines for large scale foundation model training.

  • Contribute to experiments, including designing experimental details, writing reusable code, running model evaluations, and organizing results.

  • Contribute to publications and open-sourcing efforts.

Minimum Qualifications

  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.

  • Research experience in machine learning, robotics, computer vision and natural language processing.

  • Experience with developing robotics algorithms or machine learning models at scale.

  • Programming experience in Python/C++. Good understanding of deep learning frameworks like Pytorch or Jax.

  • Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.

Desired Qualifications

  • Master's/PhD in Robotics, Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.

  • Direct experience in robotics, computer vision, or machine learning research. Experience with the Transformer model architecture.

  • First author publications at peer-reviewed AI and robotics conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICRA, IROS).

  • Experience with high fidelity simulation platforms such as AirSim, CARLA, Isaac Sim among others.

  • Experience building efficient robotics pipelines involving sensor fusion and model inference.

  • Good understanding of systems considerations and the ability to factor these into model choices.

Average salary estimate

$110000 / YEARLY (est.)
min
max
$90000K
$130000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Research Engineer, Manipulation, Scaled Foundations

Are you ready to dive into the exciting world of robotics? Scaled Foundations, an innovative AI research and deployment company, is on the hunt for a passionate Research Engineer in Manipulation to join our dynamic team in Redmond. As part of our mission to build general robot intelligence, you will play a crucial role in shaping the next wave of robotic foundation models that perform across various forms like aerial and ground-based systems. We're looking for someone with a solid background in robotics and machine learning, particularly experienced in multimodal machine learning and synthetic data generation through simulation. In your role as a Research Engineer, you'll be designing cutting-edge tools and infrastructure to enhance robotic manipulation capabilities. You'll have the chance to define impactful research goals, leverage high-fidelity simulation for data generation, and create robust training pipelines for large-scale model training. If you have skills in reinforcement learning and a knack for adapting machine learning frameworks to real-world manipulation applications, we want to hear from you! Bring your Python or C++ programming expertise and your knowledge of deep learning frameworks like PyTorch or JAX, and help us shape the future of robotics. At Scaled Foundations, you’ll not only contribute to ground-breaking experiments but also have the opportunity to share your findings through publications and open-source projects. If you're eager to push the boundaries and work alongside some of the brightest minds in robotics, this is the perfect place for you to thrive!

Frequently Asked Questions (FAQs) for Research Engineer, Manipulation Role at Scaled Foundations
What are the qualifications needed for a Research Engineer at Scaled Foundations?

To qualify as a Research Engineer at Scaled Foundations, candidates should possess at least a Bachelor's degree in Computer Science, Computer Engineering, or a relevant field. We're also looking for research experience in areas like machine learning, robotics, computer vision, or natural language processing. Furthermore, familiarity with robotics algorithms and machine learning models, programming skills in Python or C++, and understanding deep learning frameworks like PyTorch or JAX are essential.

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What does a Research Engineer in Manipulation do at Scaled Foundations?

As a Research Engineer in Manipulation at Scaled Foundations, you'll be at the forefront of designing methods and tools that advance robotic manipulation techniques. This includes defining research goals that accommodate real-world engineering challenges and adapting standard machine learning models for manipulation applications. You will also collaborate on experiments, write clean reusable code, and contribute to publications that share our innovations with the robotics community.

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Can I work remotely as a Research Engineer at Scaled Foundations?

The role of Research Engineer in Manipulation at Scaled Foundations requires on-site collaboration in Redmond. While our work is heavily team-oriented and benefits from being in close proximity to your colleagues, we do understand the need for flexibility and will consider remote work arrangements for exceptional candidates on a case-by-case basis.

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What programming languages are required for the Research Engineer position at Scaled Foundations?

For the Research Engineer position in Manipulation at Scaled Foundations, proficiency in programming languages such as Python and C++ is required. Having a solid understanding of these programming languages will allow you to effectively develop robotics algorithms and machine learning models, which are critical for your success in this role.

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What research areas should I be familiar with to apply for the Research Engineer role at Scaled Foundations?

Ideal candidates for the Research Engineer position at Scaled Foundations should have research experience in multiple areas, including robotics, machine learning, computer vision, and natural language processing. Being knowledgeable in reinforcement learning, synthetic data generation through simulation, and the capabilities of high-fidelity simulation platforms is also critical for succeeding in this role.

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How does Scaled Foundations support the professional growth of Research Engineers?

Scaled Foundations is committed to the professional development of our team members. As a Research Engineer in Manipulation, you'll have numerous opportunities to take part in cutting-edge research projects and collaborations. We encourage our engineers to contribute to publications, engage in open-source initiatives, and continuously learn the latest advancements in robotics and AI technologies.

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What types of machine learning frameworks are beneficial for the Research Engineer position at Scaled Foundations?

For the Research Engineer role at Scaled Foundations, familiarity with deep learning frameworks such as PyTorch and JAX is crucial. Experience with these frameworks will enable you to adapt machine learning models for manipulation tasks and implement advanced techniques that are necessary for pushing the boundaries of robotic intelligence.

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Common Interview Questions for Research Engineer, Manipulation
Can you explain your experience with machine learning and robotics?

When answering this question, highlight specific projects where you used machine learning in robotics. Discuss the algorithms you implemented, the challenges you encountered, and how you overcame them. Providing concrete examples will demonstrate your expertise and practical experience.

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What do you know about high-fidelity simulation platforms?

In your response, discuss various high-fidelity simulation platforms you've worked with, such as AirSim or CARLA. Explain how these platforms aid in data generation for training machine learning models in robotics, and emphasize any practical experiences you have had in utilizing them to enhance robotic manipulation.

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How do you approach defining research goals in your projects?

Explain your methodology for setting research goals by considering both the potential impact of the research and the real-world engineering constraints. Elaborate on how you ensure your goals align with the broader objectives of your team OR company, while also addressing any feedback from stakeholders.

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Describe a successful project where you applied synthetic data generation.

Share details about a specific project where synthetic data generation played a crucial role. Discuss the techniques you employed, the challenges you faced, and the outcome of the project. Highlight metrics that showcase the success of your work, demonstrating its relevance and impact on your project.

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What are the key considerations when building a sim2real pipeline?

When discussing sim2real pipelines, mention the importance of domain adaptation techniques, accuracy in physics simulation, and the critical role of validation in bridging the gap between simulations and real-world applications. Share any experiences you have had in implementing strategies for effective sim2real transfers.

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What types of machine learning models have you adapted for robotic applications?

In your answer, provide examples of machine learning models you've adapted for robotics tasks, and elaborate on how you tailored these models to suit specific application needs. Describe the impact these adaptations had on the performance and efficiency of the robotic systems.

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Can you discuss your programming experience and any frameworks you have encountered?

Highlight your programming experience in Python and C++, mentioning any specific frameworks you've used in your projects, such as TensorFlow or PyTorch. Explain how your knowledge in these areas has streamlined your work in machine learning and robotics.

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Have you authored any publications in your field? If so, describe one.

If applicable, share details about your first-author publications at peer-reviewed conferences. Discuss the focus of your research, methodologies employed, and the significance of the findings to the field of robotics. This shows you can contribute to the academic aspect of the industry.

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What are the challenges you think the field of robotics is currently facing?

Discuss various challenges such as the integration of AI in robotics, real-time decision-making, and safety considerations. Provide thoughtful insights on how these challenges can be approached or mitigated, showing your understanding of the current industry landscape.

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How do you stay updated with the latest developments in robotics and AI?

Mention the resources and methods you use to stay informed, such as academic journals, online courses, conferences, or networking within professional circles. This indicates your commitment to professional growth and staying relevant in your field.

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Full-time, on-site
DATE POSTED
November 29, 2024

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