Computer Vision Engineer

Who we are

Samsara (NYSE: IOT) is the pioneer of the Connected Operations Cloud, which allows businesses that depend on physical operations to harness IoT (Internet of Things) data to develop actionable business insights and improve their operations. Founded in San Francisco in 2015, we now employ more than 1,600 people globally and have over 1.5 million active devices. Samsara also went public in December 2021 and we’re just getting started. 

Recent awards we’ve won include: 

• #2 in the Financial Times’ Fastest Growing Companies in Americas list 2021
• Named as a Best Place to Work in Built In 2022 
• #19 in the Forbes Cloud 100 2021  
• IoT Analytics Company of the Year in 2022’s IoT Breakthrough Winners 
• Forbes Advisor named us the Best Solution for Large Companies - Fleet management software for 2022!

We're driving change in industries that are yet to fully embrace digital transformation. Physical operations make up a massive slice of the global economy but haven’t benefited from innovation and actionable information in the way that other sectors have. The potential for scale and impact is huge.

About the role:

We operate one of the largest AI-enabled, connected vehicle fleets in the world, with hundreds of thousands of connected AI cameras in our customers’ vehicle fleets. Samsara’s Advanced Driver Assistance Systems (ADAS) rely heavily on state-of-the art machine learning tasks to perform a variety of functions, including distracted driving detection, time-to-collision estimation, lane departure warning, and more. Using a combination of proprietary Samsara data (1.6T+ sensor data points collected annually) along with open-source data sets and models, we are developing powerful ML features in both our cloud platform and on-the-edge to improve the efficiency, safety, and sustainability of our customers’ operations.

The Computer Vision Engineer will be a core technical contributor on the ML / CV team with deep expertise in building and deploying scalable machine learning and computer vision solutions. The Computer Vision Engineer will work closely with full-stack, firmware, and infrastructure / platform teams to build and deploy powerful computer vision features for our customers.

In this role, you will: 

• Build and improve the accuracy of ML / CV models, including retraining and optimizing open-source models to solve Samsara-specific problems 
• Shape Samsara’s big data into features for ML / CV models (e.g., using image data from our dashcams to build models supporting advanced safety features)
• Build the backend or edge infrastructure to scale our training and inference workload, including training pipelines, evaluation, and model deployment
• Stay connected to industry and academic research and adopt novel technology that suits Samsara’s needs
• Champion, role model, and embed Samsara’s cultural principles

Minimum requirements for the role:

• M.S., Ph.D. in Computer Science, Statistics, or a related quantitative field; or BS with 2+ years experience as a Data Scientist, Applied Scientist,  Machine Learning Engineer, or similar role
• Strong proficiency in common languages (e.g., Python, SQL) and tools (e.g., TensorFlow, PyTorch, distributed training / inference with Spark) in the ML toolkit
• Deep understanding of deep learning, image classification, object detection and segmentation
• Experience building and deploying large-scale machine learning models with feedback loops for continuous improvement
• Experience building performant, distributed training and inference pipelines on very large datasets
• Comfortable with full-stack / backend development code to build a strong understanding of underlying data structures and other dependencies (For reference: We use Golang for our backend, Typescript and React for our web client, GraphQL to fetch data from our backend, and React Native for our mobile app)

An ideal candidate also has:

• Preferred: Experience building, deploying, and optimizing ML models on the edge
• Preferred: Experience with perception algorithms in a real-time environment
• Preferred: MS / PhD in engineering or quantitative discipline (e.g., Statistics, Mathematics, Computer Science, Economics, etc.)

This role can be office-based or fully remote in the US and Canada.

#LI-Remote

At Samsara, we welcome everyone regardless of their background, race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, etc. We depend on the unique approaches of our team members to help us solve complex problems. We are committed to increasing diversity across our team and ensuring that Samsara is a place where people from all backgrounds can make an impact.

Accommodations

Samsara is an inclusive work environment, and we are committed to ensuring equal opportunity in employment for qualified persons with disabilities. Please email accessibleinterviewing@samsara.com or click here if you require any reasonable accommodations throughout the recruiting process.

US Only: Please note that Samsara’s COVID-19 vaccination policy requires all team members who will be meeting in person for business or working from one of our offices to be fully vaccinated against COVID-19. People who cannot be vaccinated for qualifying medical conditions, sincerely held religious beliefs, and other legally protected categories, may request an accommodation.

Benefits

Our target total compensation market position is in the top 25% of all software and hardware companies. Our full time employees receive an above market-rate salary, an outstanding equity offering, employee-led remote and flexible working, health benefits, personal development, Samsara for Good charity fund, and much, much more. Take a look at our Benefits site to learn more.  

Flexible Working 

At Samsara, we have adopted a flexible way of working, enabling teams and individuals to do their best work, regardless of where they’re based. We value in-person collaboration and know a change of scenery and quiet space to work is welcomed from time to time, but also appreciate that the world of work has changed. Our offices remain open for those who prefer to collaborate or work in-office, but we also encourage fully remote applicants.