Senior Software Engineer, Controls

As a Senior Software Engineer at Plus, essential responsibilities include designing and implementing control algorithms, enhancing frameworks that integrate model predictive control (MPC) with learning-based approaches, and developing machine-learning vehicle models. You'll collaborate with domain experts to solve trajectory tracking challenges and ensure that all models function efficiently in real-time environments. Additionally, you'll take the lead in vehicle testing and analysis, helping shape the future of our autonomy technology.

To be considered for the Senior Software Engineer role at Plus, candidates should hold a Master's or PhD in Mechanical Engineering, Robotics, Aerospace Engineering, Computer Science, or a related field. A minimum of two years of machine learning experience or relevant industry background in robotics applications is required. A solid understanding of motion control, programming skills in Python and C++, and experience with modern model development frameworks like PyTorch are also essential.

Plus offers numerous opportunities for professional development and career growth for Senior Software Engineers. You'll work in an innovative environment where you'll continually learn from cross-functional teams and latest technologies. The company is committed to supporting your personal and professional journey, enhancing your skillset and allowing you to take on increasing responsibilities.

Collaboration is at the core of Plus's culture. As a Senior Software Engineer, you'll work closely with engineers, research scientists, and domain experts in multidisciplinary teams. Regular meetings, brainstorming sessions, and project collaborations ensure that everyone’s insights are valued and contribute to our shared goal of advancing autonomous vehicle technology.

The salary range for a Senior Software Engineer at Plus is between $150,000 and $200,000 per year. Exact compensation may vary based on skills and experience. Plus also provides a highly competitive benefits package, including a 401(k) plan, to support your financial well-being.

When discussing your experience with motion control, emphasize specific projects you've worked on involving motion control systems. Mention any algorithms you developed, challenges you faced, and how you successfully implemented solutions, showcasing your technical skills and understanding of real-time operations.

In answering this question, describe your hands-on experience with PyTorch, including any projects where you implemented machine learning models. Discuss how you utilized PyTorch’s capabilities for model training, evaluation, and optimization, and share outcomes that demonstrate your proficiency.

When addressing your debugging approach, provide a systematic framework you follow, such as isolating variables, replicating issues, and utilizing diagnostic tools. Share specific examples of past debugging experiences to illustrate your problem-solving skills and attention to detail.

Discuss your strategies for real-time control systems, such as prioritizing latency and efficiency, leveraging understandings of system dynamics, and implementing model predictive control methods. Share any projects where you successfully applied these strategies to meet performance requirements.

In your response, highlight your familiarity with vehicle dynamics principles and any direct experience with drive-by-wire systems. Explain how this knowledge has influenced your past projects or roles and how it informs your approach to developing control systems for autonomous vehicles.

Identify potential challenges such as safety, system reliability, or regulatory compliance. Discuss innovative solutions or methodologies you believe could mitigate these challenges, showcasing your foresight and ability to adapt to evolving technologies in the field.

Choose a project where you applied data-driven techniques effectively. However, provide details on how you used data for decision-making, model training, or performance improvement, thus showcasing your analytical skills and understanding of the importance of data in autonomous systems.

In your answer, detail your programming background in both C++ and Python, highlighting specific projects or tasks where you used each language. Discuss your proficiency levels and how you have leveraged these languages in the context of robotic systems and machine learning applications.

Emphasize the significance of teamwork in engineering by discussing how collaborative efforts enhance problem-solving, foster innovation, and lead to more robust solutions. Share an example of a successful team project you participated in, illustrating your contributions and learnings.

Describe methods you use to stay informed about the latest trends, such as reading industry publications, participating in webinars, attending conferences, or engaging with peer networks. Highlight any specific areas of interest and how this knowledge has influenced your work.