Senior, Machine Learning Engineer - Annotation Automation

About the Company

At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business.

A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family, we are focused solely on developing software for automated trucks to transform how the world moves freight.

Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.

Meet the Team:  

We are the annotation automation team to accelerate the creation of annotations by auto labeling and working with internal and external parties. To support various ML model developments for self-driving, we need to create datasets that shall be cleaned, balanced, and annotated. The team develops various pipelines for camera lidar object detection, tracking and fusion as well as HD map creations. We also deploy our pipelines on AWS to process large scale dataset.    

What you'll do:  

• Design, implement, test and deploy offline object detection, tracking and fusion modules to automatically create annotations on AWS from logged sensor data (Cameras, Lidars, Radars) 
• Enhance and improve our existing auto labeling pipelines for various use cases
• Long range object detection and tracking 
• Deploy and optimize the performance of the cloud-based auto labeling pipelines    
• Contribute to the research, development, and improvement of data centric AI pipelines
• Participate in team meetings to share progress, collaborate on new ideas, and address any challenges
• Stay up to date with the latest developments in AI and ML for autonomous driving.  
• Participate in technical discussions, brainstorming sessions, and other team meetings.  
• Develop and maintain thorough documentation for all developed pipelines and tools.  

What you’ll need to Succeed:  

• Bachelor’s Degree in Computer Science, Robotics, Electrical Engineering or related technical field plus demonstrates competences and technical proficiencies typically acquired through 6+ years of experience OR Master’s Degree in Computer Science, Robotics, Electrical Engineering or related technical field plus demonstrates competences and technical proficiencies typically acquired through 3+ years of experience
• Strong coding skills
• Advanced data structure and algorithms
• Cloud computing  
• Proven experience designing and developing ML models  
• Familiar with at least one deep learning framework such as TensorFlow or PyTorch  
• Hands-on experience with deep learning and computer vision
• Prior experiences in object detection, segmentation, tracking and fusion
• Strong communication skills, able to articulate complex concepts to diverse audiences  
• Excellent problem-solving skills and the ability to work in a fast-paced, dynamic environment 

Bonus Points!  

• Doctorate Degree
• Advanced AWS skills
• Data centric AI experience  
• DNN model optimization such as TensorRT and ONNX
• Publication record in top venues in computer vision and/or machine learning, e.g. CVPR, ICCV, ICRA, IROS, ECCV, NeurIPS, and SIGGRAPH. 

Perks of Being a Full-time Torc’r

Torc cares about our team members and we strive to provide benefits and resources to support their health, work/life balance, and future. Our culture is collaborative, energetic, and team focused. Torc offers:

• A competitive compensation package that includes a bonus component and stock options
• 100% paid medical, dental, and vision premiums for full-time employees
• 401K plan with a 6% employer match
• Flexibility in schedule and generous paid vacation (available immediately after start date)
• Company-wide holiday office closures
• AD+D and Life Insurance

At Torc, we’re committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our Torc’rs and do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, veteran status, or disabilities.

Even if you don’t meet 100% of the qualifications listed for this opportunity, we encourage you to apply.