Join TuSimple and help change the way the world moves.  Together we're making freight transportation safer, more efficient, and more environmentally friendly.

Company Overview

Come join a higher calling and find a deeper purpose!

As a multi-national Artificial Intelligence Technology Company, we are at the epicenter of the Autonomous Vehicle Universe. Our breakthroughs are leading the industry in autonomous trucking.

While inventing the framework of Autonomous Driving, our current fleet of autonomous Trucks are helping communities receive much-needed supplies and medical equipment around the clock.   Our people are some of the most talented engineers and contributors who are leaving behind a historic legacy.

TuSimple was founded half a decade ago with the goal of bringing the top minds in the world together to achieve the dream of a driverless truck solution. With a foundation in computer vision, algorithms, mapping, and Artificial Intelligence, TuSimple is working to create the first global commercially viable Autonomous Freight Network.

Job Description

The ML Infrastructure team is aimed at building industry leading ML platform solutions for TuSimple data scientists and machine learning engineers to easily and quickly apply ML to a diverse set of use cases, at scale. An example of a core tool that we build and maintain includes a user-friendly platform to train large AI models quickly and cost effectively.

Responsibilities

• Work on machine learning infrastructure solutions to build a world-class platform to enable the future of autonomous driving
• Build high performance and flexible infrastructure and services that can rapidly evolve to handle new technologies, techniques and modeling approaches
• Work closely with data scientists and machine learning domain experts to implement production ready systems for processing data, running experiments, managing model artifacts / versions, etc.
• Own the development and maintenance of critical core machine learning platform software stacks
• Provide architecture and technical direction for frontend and backend systems

Key Qualifications

• 5+ years of software engineering industry experience
• Hands on experience with HPC for AI in cloud environments using open-source platforms such as KubeFlow or MLFlow and/or proprietary solutions such as AWS SageMaker or Google Cloud AI
• Experience building ML training platforms and pipelines to deliver distributed (multi-node) training solutions for data scientists and ML engineers
• Experience developing production quality backend services using frameworks such as Spring, Quarkus, or similar
• Experience with key infra technologies like Kubernetes, databases, and cloud vendors (AWS preferred)
• Proficiency in at least one statically typed programming language such as Java or C++ and at least one scripting language such as Python.

Preferred Qualifications

• Prior experience in machine learning - you've developed and deployed your own models - even if these are simple proof of concepts
• Hands on experience with machine learning development lifecycles for computer vision / perception, from data collection to automated model fine tuning
• Experience with big data technologies such as Spark, AirFlow, Hadoop, etc.
• Relevant experience in autonomous driving

TuSimple Benefits

• 100% employer-paid healthcare premiums for you and your family
• Work visa sponsorship available
• Relocation assistance available
• Breakfast, lunch, and dinner served every day
• Full kitchens on every floor with unlimited snacks, drinks, special treats, fruits, meals, and more
• Stock options / equity
• Gym membership reimbursement
• Monthly team building budget
• Learning/education budget
• Employer-paid life insurance
• Employer-paid long and short disability

TuSimple is an Equal Opportunity Employer. This company does not discriminate in employment and personnel practices on the basis of race, sex, age, handicap, religion, national origin or any other basis prohibited by applicable law. Hiring, transferring and promotion practices are performed without regard to the above-listed items.