Senior AI Engineer, Neural Simulator

The Senior AI Engineer role at Path Robotics involves developing advanced AI-driven robotic solutions by creating multimodal neural simulators specifically designed for manufacturing tasks. This position requires expertise in full-stack AI engineering, focusing on data pipelines, model training, and deployment, as well as designing large-scale models for robotic perception and control.

To be a suitable candidate for the Senior AI Engineer position at Path Robotics, you should possess at least 5 years of experience in machine learning, deep learning, and robotics applications. Proficiency in Python and familiarity with ML frameworks such as JAX, PyTorch, and TensorFlow are essential. Additionally, experience with neural simulators and large-scale model training is highly desirable.

The culture at Path Robotics is built on collaboration, kindness, and innovation. As a Senior AI Engineer, you'll work alongside a team that is committed to tackling tough challenges and values unique ideas. The company is dedicated to providing a diverse and inclusive environment where all team members are respected and their contributions are recognized.

As a Senior AI Engineer at Path Robotics, you can expect to work on projects that involve training video generation models, developing neural simulators, and creating world models for robotic systems. Your work will focus on pushing the boundaries of AI technology to improve robot fleet performance in manufacturing settings.

Path Robotics provides a robust benefits package that includes free lunch, flexible PTO, comprehensive medical, dental, and vision insurance, with 100% coverage on select plans. Additionally, the company offers a generous parental leave policy, a 401K plan, and a paid referral bonus, making it a great place to work.

When discussing your experience with neural simulators, be specific about projects you've worked on where you developed or used such tools. Highlight the technologies employed, the challenges you faced, and how your contributions positively impacted the projects.

Talk about a specific project where you managed the deployment of a large-scale AI model. Focus on the methodologies you used, the obstacles you encountered, and how you ensured the model's performance met or exceeded expectations post-deployment.

Discuss common pitfalls such as overfitting, inadequate data quality, and insufficient model validation. Stress the importance of thorough testing and continuous iteration to address these issues, emphasizing your strategies for avoiding them in your past projects.

Explain how you stay informed about advancements in generative AI, such as following key research publications, participating in conferences, or engaging with communities. Share specific resources or networks you're involved in and any major breakthroughs that have influenced your work.

Discuss how you've utilized Python in various aspects of AI engineering, from building machine learning models to creating data pipelines. Highlight specific libraries or frameworks you're familiar with, such as TensorFlow or PyTorch, and how they facilitated your work.

Share a story about a collaborative project where teamwork was critical to success. Focus on your role, how you communicated with team members, and how different skill sets were integrated to achieve the project's goals.

Describe the approaches you've taken to optimize models for robotics, such as fine-tuning hyperparameters, implementing efficient algorithms, and testing various architectures. Discuss how you evaluate a model's performance and ensure it meets real-world requirements.

Identify significant challenges you've experienced in previous robotics AI projects, such as hardware limitations or integration dilemmas. Explain how you approached these problems and what you learned from them, showing your resilience and adaptability.

When answering this question, express your enthusiasm for Path Robotics' mission to innovate in the manufacturing sector. Discuss how your personal and professional values align with the company’s goals and culture, and why you believe you’d bring valuable contributions to the team.

Share your commitment to continuous learning by highlighting the courses, workshops, or self-study methods you employ to stay up-to-date. Concentrate on how this mindset benefits your role and contributes to your skill set as a Senior AI Engineer.