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- Tasks: Design and optimise AI models for edge devices, ensuring real-time performance.
- Company: Field AI is revolutionising robotics with cutting-edge AI systems for real-world applications.
- Benefits: Enjoy a competitive salary, hybrid work options, and a collaborative team environment.
- Why this job: Join a world-class team tackling complex challenges in robotics and AI deployment.
- Qualifications: 3+ years in AI model development; proficiency in PyTorch, C++, and CUDA required.
- Other info: Diversity and inclusion are core values; all candidates evaluated on merit.
The predicted salary is between 49000 - 84000 £ per year.
1.12 Senior AI Software Engineer — Edge Model Optimization & Deployment
1.12 Senior AI Software Engineer — Edge Model Optimization & Deployment
2 days ago Be among the first 25 applicants
Field AIis transforming how robots interact with the real world. We are building risk-aware, reliable, and field-ready AI systems that address the most complex challenges in robotics, unlocking the full potential of embodied intelligence. We go beyond typical data-driven approaches or pure transformer-based architectures, and are charting a new course, with already-globally-deployed solutions delivering real-world results and rapidly improving models through real-field applications.
Field AIis transforming how robots interact with the real world. We are building risk-aware, reliable, and field-ready AI systems that address the most complex challenges in robotics, unlocking the full potential of embodied intelligence. We go beyond typical data-driven approaches or pure transformer-based architectures, and are charting a new course, with already-globally-deployed solutions delivering real-world results and rapidly improving models through real-field applications.
What You’ll Get To Do:
- Design, implement, and optimize 2D/3D CNN and Transformer-based models for deployment on edge and embedded platforms (e.g., NVIDIA Jetson)
- Apply model compression techniques such as quantization, pruning, distillation, and weight sharing to achieve efficient real-time inference under strict constraints on power, bandwidth, and latency
- Convert, compile, and optimize neural networks for runtime using TensorRT , ONNX , CUDA , and C++
- Develop and maintain ROS nodes and interfaces that integrate perception models with the broader robotic system
- Collaborate closely with AI researchers, robotics engineers, and hardware teams to translate cutting-edge research into deployable solutions on edge devices
- Build benchmarks, profile and debug runtime issues, and validate performance against real-world scenarios
- Ensure the reliability, robustness, and stability of deployed models operating in challenging, resource-constrained environments
What You Have:
- 3+ years of professional experience in developing and deploying deep learning models for edge, embedded, or real-time systems
- BS, MS, PhD, or equivalent in Computer Science, Robotics, Electrical Engineering, or a related field
- Strong proficiency in PyTorch , C++ , Python , and CUDA for AI/ML development and model optimization
- Hands-on experience with TensorRT , ONNX , TVM , or similar toolchains and compilers for edge deployment
- Proven track record applying model optimization techniques (quantization, pruning, distillation)
- Deep understanding of hardware limitations and performance tuning for Jetson , ARM , GPUs, or other embedded platforms
- Experience integrating AI models into ROS -based robotic systems
- Skilled in profiling and debugging GPU workloads, with familiarity using tools like Nsight or CUPTI
- Ability to work independently and collaboratively within cross-functional teams in a fast-paced, iterative environment
The Extras That Set You Apart:
- Familiarity with JAX or additional ML frameworks beyond PyTorch
- Experience with compiler-level optimizations for GPU inference
- Background in deploying AI solutions for real-time robotics operating in the field
Compensation and Benefits
Our salary range is generous ($70,000 – $200,000 annual), but we take into consideration an individual\’s background and experience in determining final salary; base pay offered may vary considerably depending on geographic location, job-related knowledge, skills, and experience. Also, while we enjoy being together on-site, we are open to exploring a hybrid or remote option.
Why Join Field AI?
We are solving one of the world’s most complex challenges: deploying robots in unstructured, previously unknown environments. Our Field Foundational Models set a new standard in perception, planning, localization, and manipulation, ensuring our approach is explainable and safe for deployment.
You will have the opportunity to work with a world-class team that thrives on creativity, resilience, and bold thinking. With a decade-long track record of deploying solutions in the field , winning DARPA challenge segments, and bringing expertise from organizations like DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise Self-Driving, Zoox, Toyota Research Institute, and SpaceX, we are set to achieve our ambitious goals.
Be Part of the Next Robotics Revolution
To tackle such ambitious challenges, we need a team as unique as our vision — innovators who go beyond conventional methods and are eager to tackle tough, uncharted questions. We’re seeking individuals who challenge the status quo, dive into uncharted territory, and bring interdisciplinary expertise. Our team requires not only top AI talent but also exceptional software developers, engineers, product designers, field deployment experts, and communicators.
We are headquartered in always-sunny Mission Viejo (Irvine adjacent), Southern California and have US based and global teammates.
Join us, shape the future, and be part of a fun, close-knit team on an exciting journey!
We celebrate diversity and are committed to creating an inclusive environment for all employees. Candidates and employees are always evaluated based on merit, qualifications, and performance. We will never discriminate on the basis of race, color, gender, national origin, ethnicity, veteran status, disability status, age, sexual orientation, gender identity, martial status, mental or physical disability, or any other legally protected status.
Seniority level
-
Seniority level
Not Applicable
Employment type
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Employment type
Full-time
Job function
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Job function
Engineering and Information Technology
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1.12 Senior AI Software Engineer — Edge Model Optimization & Deployment employer: Field AI
Contact Detail:
Field AI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land 1.12 Senior AI Software Engineer — Edge Model Optimization & Deployment
✨Tip Number 1
Familiarise yourself with the specific technologies mentioned in the job description, such as TensorRT, ONNX, and CUDA. Having hands-on experience with these tools will not only boost your confidence but also demonstrate your readiness to tackle the challenges of the role.
✨Tip Number 2
Engage with the robotics and AI community online. Join forums, attend webinars, or participate in relevant discussions on platforms like GitHub or LinkedIn. This can help you stay updated on industry trends and may even lead to valuable connections that could support your application.
✨Tip Number 3
Prepare to discuss your previous projects in detail, especially those involving edge deployment and model optimisation. Be ready to explain the challenges you faced and how you overcame them, as this will showcase your problem-solving skills and practical experience.
✨Tip Number 4
Research Field AI's current projects and their approach to robotics. Understanding their mission and values will allow you to tailor your conversations during interviews, showing that you're genuinely interested in contributing to their goals.
We think you need these skills to ace 1.12 Senior AI Software Engineer — Edge Model Optimization & Deployment
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in AI, deep learning, and edge deployment. Focus on specific projects where you've implemented model optimization techniques like quantization or pruning.
Craft a Compelling Cover Letter: In your cover letter, express your passion for robotics and AI. Mention how your skills align with the company's mission to deploy robots in unstructured environments and provide examples of your past work that demonstrate your capabilities.
Showcase Technical Skills: Clearly list your technical proficiencies, especially in PyTorch, C++, Python, and CUDA. If you have experience with TensorRT or ONNX, make sure to highlight that as well, as it’s crucial for this role.
Demonstrate Collaborative Experience: Since the role involves working closely with cross-functional teams, include examples of past collaborations with AI researchers or engineers. Highlight any successful projects that required teamwork and communication.
How to prepare for a job interview at Field AI
✨Showcase Your Technical Skills
Be prepared to discuss your experience with deep learning models, particularly in edge and embedded systems. Highlight specific projects where you've implemented model optimization techniques like quantization or pruning, and be ready to explain the impact of these techniques on performance.
✨Demonstrate Collaboration Experience
Since the role involves working closely with AI researchers and robotics engineers, share examples of how you've successfully collaborated in cross-functional teams. Discuss any challenges you faced and how you overcame them to achieve a common goal.
✨Familiarise Yourself with Relevant Tools
Make sure you are well-versed in tools like TensorRT, ONNX, and CUDA. Be ready to discuss how you've used these tools in past projects, and consider preparing a brief demonstration or explanation of how you would optimise a neural network for deployment.
✨Prepare for Problem-Solving Questions
Expect to face technical questions that assess your problem-solving skills, especially in real-time scenarios. Practice articulating your thought process when debugging GPU workloads or optimising models under strict constraints, as this will showcase your analytical abilities.
