Staff Software Engineer, Stack AV
Motion Planning ML
Autonomous systems for the transportation industry
Open for applications
Autonomous systems for the transportation industry
201-500 employees
Open for applications
201-500 employees
Company mission
To revolutionize the transportation industry through the deployment of advanced autonomous systems.
Role
Who you are
- Candidates need to understand, experiment, improve, and field state-of-the-art motion planning machine learning systems in real-time, safety-critical applications
- Candidates should have a mission-driven mindset and customer-centric obsession to deliver a compelling product, and be able to work with significant cross-functional interactions
- Experience architecting, training, and deploying machine learned models. Specific areas of focus: Scene-level behavior prediction models
- Joint prediction-planning models
- Motion planning models
- Experience building motion planning systems for real world applications with a strong understanding of the pros and cons of various approaches
- Knowledge and experience with real-time algorithms, and machine learning approaches
- Strong experience in software engineering and algorithm design
- Fluent in C++ and Python
- Experience with standard ML toolchain (PyTorch / TensorFlow, training framework, experiment managers, distributed training, ONNX / TensorRT)
What the job involves
- We are looking for strong software and machine learning engineers to help in developing and deploying motion planning components for next generation self-driving systems
- This requires strong ownership over critical components
- We are focused on building a product
- Own delivery of motion planning modules that solve on-vehicle problems and deliver for customer needs - meeting product requirements and meeting the needs of the controls system, providing a safe, smooth trajectory for the system to follow
- Design, scope, implement, and integrate machine learning systems to solve on-vehicle behavior problems in a real-time, resource-constrained environment
- Provide input in the technical direction for the team, and work cross-functionally to develop safe systems. This will include working closely with other teams such as perception, localization, and controls to ensure that the input to the motion planning modules is appropriate
- Work closely with systems engineers to ensure a safe, well tested product is delivered
- Work closely with verification teams to ensure proper testing and validation of the motion planning modules. Make extensive use of unit testing, simulation, and log simulation to properly validate their work
- Spend time on the vehicles to experience in person the efforts being worked
- Provide input to team roadmaps and ensure product features are properly prioritized
- Identify bottlenecks and limitations in system performance, and develop novel motion planning components to unlock new capabilities and ensure a reliable system
- Be involved in experimentation, design and iteration exercises, and help to align stakeholders by using strong presentation and communication skills
Our take
Driver shortages, decelerating efficiency and broad safety concerns have plagued the US trucking industry for some time now. High operating costs paired with increasingly scrutinized high emissions are leading to concern over the future of the logistics and goods transport market. Stack AV’s autonomous trucking solution aims to lighten the load of these issues, using AI to create smart supply chains and autonomous driving systems.
Its founding team have long been exploring the possibilities of autonomous transport through combined experience with Uber, and Google smart cars and shared founding roles at Argo AI, a similar company that disbanded in 2022 after it failed to become profitable for shareholders. Hopefully, however, the launch of Stack AV will balance the decades of experience as well as hard lessons learnt from the failed predecessor company and will find new ways to make autonomous driving tech a sustainable investment.
With a staggering $1 billion invested in Stack AV by SoftBank in 2023, the company is well-armoured for the time being. Its main competitor is Aurora, which underwent a successful IPO in 2021 but never achieved the high level of early funding that Stack AV did. It’s a promising start then for the Argo AI veterans' new venture.
Kirsty
Company Specialist at Welcome to the Jungle
Company
Funding (1 round)
Sep 2023
$1bn
SERIES A
Total funding: $1bn
Company values
- SAFETY - Safety is our top priority. Individually and collectively, we embrace our obligation to be responsible and ensure that safety is our company's bedrock
- HUMILITY - We operate with respect for all, and are humble in our achievements and mistakes. We take ownership of our conduct, embrace one another's differences, and uphold an environment of kindness and dignity
- We operate with respect for all, and are humble in our achievements and mistakes. We take ownership of our conduct, embrace one another's differences, and uphold an environment of kindness and dignity
- GRIT - The path to success is rarely straight or smooth. We succeed as a team through disciplined execution, working together to understand the problems at a fundamental level and developing thoughtful and practical solutions
- EXCELLENCE - As a team, we execute and deliver a world class product that brings value to our customers by solving their critical business needs in a safe and efficient manner. Our accomplishments together are greater than any effort individually
- TRANSPARENCY - We are transparent and honest about the facts of our execution and hold ourselves accountable to drive real, continuous improvement through our work and to foster public trust and support of our products and services
- PASSION - We are passionate about our mission, and our culture. Our passion motivates our success and creates an environment where our teams thrive
Company HQ
Downtown, Pittsburgh, PA
Articles
Leadership
Brian Salesky
(CEO)Previously CEO of Argo AI, Director of Hardware Development for self-driving cars at Google, Principal Commercialization Specialist at the National Robotics Engineering Center, and Technical Program Manager at Google.
Peter Rander
(President)Previously President and Co-Founder at Argo AI, Engineering Lead at Uber and Principal Commercialization Specialist at the National Robotics Engineering Center.
Brett Browning
(CTO)Previously CTO at Argo AI, Senior Engineering Manager at Uber Advanced Technologies Center, Co-Founder at Mine Vision Systems and a Senior Systems Scientist at Carnegie Mellon University.
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