Senior Machine Learning Engineer

Who we are

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 ML Experience team builds end-to-end ML applications to power different product pillars at Samsara. As a Senior Machine Learning Engineer II, you will be responsible for developing ML solutions to increase the safety, efficiency and sustainability of the physical operations. You will work closely with various engineering teams across ML, full-stack, firmware as well as cross functional partners to deliver core infrastructure, services, and optimizations.

This is a remote position open to candidates residing in 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 world's 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:  

• Design and implement scalable machine learning infrastructure using Ray to support model training, deployment, and inference at scale.
• Leverage Kubernetes for orchestration of containerized applications, ensuring seamless deployment, scaling, and management of ML models and associated services.
• Develop and maintain CI/CD pipelines for automated testing, deployment, and management of ML applications and infrastructure.
• Implement robust monitoring, logging, and alerting systems to ensure high availability, performance, and security of the ML platform.
• Collaborate with data scientists and ML engineers to optimize data pipelines and model performance.
• Stay abreast of the latest advancements in machine learning technologies and infrastructure, and advocate for the adoption of best practices and new technologies within the team.
• Provide DevOps/SRE support for the ML platform, including incident response, performance tuning, and disaster recovery planning.
• 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:

• BS or MS in Computer Science or other relevant field.
• 6+ years of experience as a Machine Learning Engineer, Applied Scientist, or similar role.
• Strong proficiency in one or more common languages (e.g., C++, Golang, Java, Python, Scala).
• Proficiency with common ML tools (e.g., Spark, TensorFlow, PyTorch).
• Experience deploying and iteratively refining models using customer feedback loops.
• Comfortable with full-stack / backend development code to build a strong understanding of underlying data structures and other dependencies.

An ideal candidate also has:

• Ph.D. in Computer Science or quantitative discipline (e.g., Applied Math, Physics, Statistics).
• Experience building, deploying, and optimizing ML models on the edge.
• Experience building end-to-end ML applications from scratch.
• Expertise in optimizing distributed model training with GPUs.

Samsara’s Compensation Philosophy: Samsara’s compensation program is designed to deliver Total Direct Compensation (based on role, level, and geography) that is at or above market. We do this through our base salary + bonus/variable + restricted stock unit awards (RSUs) for eligible roles. For eligible roles, a new hire RSU award may be awarded at the time of hire, and additional RSU refresh grants may be awarded annually.

We pay for performance, and top performers in eligible roles may receive above-market equity refresh awards which allow employees to achieve higher market.

The range of annual base salary for full-time employees for this position is below. Please note that base pay offered may vary depending on factors including your city of residence, job-related knowledge, skills, and experience.

$132,600—$171,600 CAD

At Samsara, we welcome everyone regardless of their background. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender, gender identity, sexual orientation, protected veteran status, disability, age, and other characteristics protected by law. We depend on the unique approaches of our team members to help us solve complex problems and want to ensure that Samsara is a place where people from all backgrounds can make an impact.

Benefits

Full time employees receive a competitive total compensation package along with employee-led remote and flexible working, health benefits, and much, much more. Take a look at our Benefits site to learn more.

Accommodations 

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

Flexible Working 

At Samsara, we embrace a flexible working model that caters to the diverse needs of our teams. Our offices are open for those who prefer to work in-person and we also support remote work where it aligns with our operational requirements. For certain positions, being close to one of our offices or within a specific geographic area is important to facilitate collaboration, access to resources, or alignment with our service regions. In these cases, the job description will clearly indicate any working location requirements. Our goal is to ensure that all members of our team can contribute effectively, whether they are working on-site, in a hybrid model, or fully remotely. All offers of employment are contingent upon an individual’s ability to secure and maintain the legal right to work at the company and in the specified work location, if applicable.

Fraudulent Employment Offers

Samsara is aware of scams involving fake job interviews and offers. Please know we do not charge fees to applicants at any stage of the hiring process. Official communication about your application will only come from emails ending in ‘@samsara.com’ or ‘@us-greenhouse-mail.io’. For more information regarding fraudulent employment offers, please visit our blog post here .