Lead Software Engineer (Rust) -Algorithmic and Optimisation (m/w/d)

As a Lead Software Engineer (Rust) at HERE Technologies, your main responsibilities include designing, implementing, and optimizing software solutions for complex logistics challenges, particularly the Vehicle Routing Problem (VRP). You will take charge of technical direction in system architecture and design, write high-performance code largely in Rust, and collaborate with cross-functional teams to ensure that your technical solutions align with product goals.

To qualify for the Lead Software Engineer (Rust) position at HERE Technologies, candidates should hold a Bachelor’s or Master’s degree in fields such as Computer Science, Mathematics, Operations Research, or related disciplines; a PhD is preferred. Additionally, 5+ years of experience in a similar role, strong programming skills in Rust (or a willingness to learn if coming from a C++ background), and expertise in algorithms, optimization, and computational mathematics are essential.

In the Lead Software Engineer (Rust) role at HERE Technologies, you will work with a cutting-edge tech stack that includes Rust, Kotlin, Python, AWS, Docker, Kubernetes, and Terraform. These tools will empower you to build scalable and high-performance systems designed to address complex logistics challenges.

HERE Technologies offers a range of benefits for the Lead Software Engineer (Rust) position, including a competitive salary plus bonuses, 30 days of paid vacation, flexible working hours, and a supportive work-life balance. You'll also have the chance to work with talented colleagues from over 60 countries and participate in exciting team events and activities.

As a Lead Software Engineer (Rust) at HERE Technologies, you will focus on projects that involve tackling logistics optimization problems, particularly the Vehicle Routing Problem (VRP), clustering, and multi-constraint routing. Your work will significantly contribute to making logistics more efficient, cost-effective, and aligned with user needs.

The Vehicle Routing Problem (VRP) involves finding the optimal routes for a fleet of vehicles to deliver goods to various locations. In an interview, demonstrate your understanding by outlining key aspects such as considering constraints like delivery windows and vehicle capacities. Discuss algorithmic approaches you might use, such as genetic algorithms, linear programming, or heuristics.

In answering this question, showcase specific algorithms you've implemented for solving logistics problems. Explain the challenges you faced, how you overcame them, and the impact of your solutions on operational efficiency. Emphasize any results or metrics that illustrate the success of your work.

Talk about your approach to writing high-quality, maintainable code, which may include practices such as code reviews, unit testing, and following clean code principles. Mention any specific methodologies or tools you use to enforce code standards and how you prioritize documentation.

Choose a specific example where you encountered a significant technical obstacle. Outline the problem, the steps you took to investigate and understand it, your proposed solution, and the results after implementing your solution. Emphasizing your problem-solving skills and resilience can make a strong impression.

In your response, highlight the resources you use to maintain your knowledge, such as online courses, forums, academic journals, or conferences. Mention any specific topics or technologies you're currently focusing on, and how applying new learnings has positively impacted your work.

Describe your experience with Rust and highlight its performance advantages, memory safety features, and concurrency capabilities. If you're transitioning from another language like C++, explain your interest in Rust and how its unique features can benefit your projects, particularly in logistics optimization.

Discuss your philosophy on collaboration, emphasizing the importance of open communication, respect for different expertise, and building strong working relationships. Provide examples of how you’ve successfully worked alongside product managers, designers, or other engineers to achieve a shared goal.

Mention metrics such as solution quality, computational time, scalability, and robustness. Elaborate on how these metrics can be used to assess the algorithm's effectiveness in solving logistics problems and how you would implement mechanisms to track and report on these metrics in your work.

Illustrate your experience with geospatial data through specific projects or technologies you've utilized. Explain how you've handled or analyzed this data to inform routing decisions, considering the unique challenges associated with geospatial information, such as coordinate systems and mapping libraries.

Highlight your ability to identify key constraints that impact routing and optimization, such as vehicle capacities and time constraints. Discuss algorithms that can flexibly adapt to these constraints and the iterative process you use to achieve effective solutions within realistic parameters.