Staff Applied Scientist at Samsara

Samsara (NYSE: IOT) is the pioneer of the Connected Operations™ Cloud, which is a platform that enables organizations that depend on physical operations to harness Internet of Things (IoT) data to develop actionable insights and improve their operations. At Samsara, we are helping improve the safety, efficiency and sustainability of the physical operations that power our global economy. Representing more than 40% of global GDP, these industries are the infrastructure of our planet, including agriculture, construction, field services, transportation, and manufacturing — and we are excited to help digitally transform their operations at scale.

Working at Samsara means you’ll help define the future of physical operations and be on a team that’s shaping an exciting array of product solutions, including Video-Based Safety, Vehicle Telematics, Apps and Driver Workflows, Equipment Monitoring, and Site Visibility. As part of a recently public company, you’ll have the autonomy and support to make an impact as we build for the long term.

About the role:

The Samsara AI team builds end-to-end AI solutions for our customers as well as core ML infrastructure for Samsara. As a Staff Applied Scientist you will be working with petabyte-scale sensor, diagnostic, video, and text data to solve critical problems for Physical Operations customers, globally. You will work closely with other scientists as well as full-stack and firmware engineers to deliver core product features, services, and optimizations.

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

You should apply if:

• You want to impact the industries that run our world: The software, firmware, and hardware you build will result in real-world impact—helping to keep the lights on, get food into grocery stores, and most importantly, ensure workers return home safely.

• You want to build for scale: With over 2.3 million IoT devices deployed to our global customers, you will work on a range of new and mature technologies driving scalable innovation for customers across industries driving the worlds physical operations.

• You are a life-long learner: We have ambitious goals. Every Samsarian has a growth mindset as we work with a wide range of technologies, challenges, and customers that push us to learn on the go.

• You believe customers are more than a number: Samsara engineers enjoy a rare closeness to the end user and you will have the opportunity to participate in customer interviews, collaborate with customer success and product managers, and use metrics to ensure our work is translating into better customer outcomes.

• You are a team player: Working on our Samsara Engineering teams requires a mix of independent effort and collaboration. Motivated by our mission, we’re all racing toward our connected operations vision, and we intend to win—together.

In this role, you will: 

• Lead design and implementation of critical AI product initiatives

• Develop both tactical AI solutions as well as more strategic and longer term research

• Work with petabyte-scale data from customer operations including text, transactions, diagnostics, sensor, camera, and location data

• Partner across business units to explore and prototype new AI experiences

• 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 (Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team) as we scale globally and across new offices

Minimum requirements for the role:

• Masters or PhD in Computer Science or other quantitative field (e.g., Applied Math, Engineering, Computer Science, Physics)

• 5+ years experience as a Scientist or Machine Learning Engineer

• Proficiency in self-serving with data for experiments and model training at scale

• Proficient with Spark, Ray, or a similar framework

• Coding in python or similar

• Strong functional knowledge of the iterative machine learning product development process

• Experienced in developing and shipping production code

• Ability to distill informal or ambiguous customer and business requirements into crisp problem definitions

• Proven ability to communicate verbally and in writing to technical peers and leadership teams with various levels of technical knowledge

• Experience coaching and mentoring scientists

An ideal candidate also has:

• PhD in Computer Science or other quantitative field

• An established record of successful high-impact deliveries in AI

• Experience building and applying ML tools and techniques to accelerate development