Senior+ Applied Scientist
WFA Digital Insight
Samsara’s Senior+ Applied Scientist sits at the intersection of massive IoT streams and actionable intelligence. The team handles more than two trillion sensor readings a year, so the role isn’t just about algorithmic elegance—it’s about turning raw telemetry into concrete safety and efficiency gains for industries that keep the economy moving. What sets this opening apart is the blend of deep technical work (machine learning, computer vision) with direct customer interaction; you’ll hear from operators on the ground, translate their pain points into model requirements, and watch those models influence real‑time dashboards. Excel may sound modest, but it’s the bridge between exploratory data work and production pipelines in a fast‑moving, remote‑first environment. Candidates should be comfortable navigating both code‑heavy research and the practical constraints of deployed hardware, because the impact is measured in reduced downtime and safer workplaces rather than abstract metrics.
Job Description
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, and Equipment Monitoring. 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 Machine Learning / Computer Vision team builds end-to-end applications to power different product pillars at Samsara. We are looking for a talented applied scientist to generate insights and draw value from rich customer interactions, as well as from the 2T+ data points our sensors and cameras collect on an annual basis.
This is a remote position open to candidates residing in the United States. This position requires travel up to 5% of the time. Relocation assistance will not be provided for this role.
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 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:
- Build and improve the accuracy of ML / CV models, including retraining and optimizing models to solve Samsara-specific problems.
- This will contribute to our R&D roadmap across our four product categories including:
- Video-based safety - Key focus.
- Vehicle telematics.
- Equipment monitoring.
- Workforce apps and Site Visibility.
- Work with petabyte-scale data from Samsara camera and sensor devices to develop new models.
- Optimize models for inference on the backend and/or on edge devices.
- Partner with firmware and full-stack teams to deploy model for optimal performance and cost.
- Stay connected to industry and academic research and adopt novel technology that suits Samsara’s needs.
- Collaborate with product team to translate customer needs to ML / CV solutions.
- 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 technical degree with 5+ years of experience as an Applied Scientist, Machine Learning Engineer, or similar role working on Computer Vision; or
- Ph.D. in Computer Science or quantitative discipline (e.g., Applied Math, Physics, Statistics) with 3+ years of experience working on Computer Vision.
- Strong proficiency in one or more common languages (e.g., C++, Golang, Java, Python).
- Proficiency with common ML tools (e.g., Spark, TensorFlow, PyTorch).
- Familiarity with managing data processing and machine learning code via GitHub.
- Excellent problem-solving skills and the ability to work alone and collaboratively.
An ideal candidate also has:
- Experience implementing ML models on large datasets 100K to 1M and more on the edge.
- Experience building, deploying, and optimizing ML models on the edge.
- Experience in state-of-the-art models for road segmentation, road object detection and tracking.
- Experience working with cross-functional teams on a project.
- Comfortable with full-stack/backend development code to build a strong understanding of underlying data structures and other dependencies.
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. This role is also eligible for an initial RSU grant with no vesting cliff, and ongoing refresh opportunities tied to performance, subject to plan terms and conditions. Learn more about our total rewards and benefits below.
Total Rewards
At Samsara, we build for the people who keep the global economy moving. We want owners, not passengers, which is why our rewards are designed to fuel high-impact builders. Our compensation program delivers above-market total compensation through a combination of base salary, performance-based bonus/variable pay, and equity (for eligible roles) in a high-growth public company. We meaningfully differentiate pay for our top performers, who have the opportunity to earn above-market compensation that can outpace the broader market over time.
Beyond compensation, we provide the foundations that enable long-term success: a flexible, employee-led remote model, a professional development stipend, comprehensive health and parental leave plans, and more. If you’re ready to build for the long term and own the outcome, your journey starts here.
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.
Belonging at Samsara
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.
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.
Our Commitment to Authenticity
We use Tofu, a fraud detection tool, to validate the authenticity of applications and protect against identity fraud. This ensures we are connecting with real people and allows us to prioritize genuine candidates. Please see Samsara’s Candidate Privacy Notice for more information.
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, @us-greenhouse-mail.io or @mail3.guide.co. For more information regarding fraudulent employment offers, please visit our blog post here.
How to Stand Out
- Highlight any projects where you turned raw sensor or video data into a deployed model; include metrics that show real‑world impact.
- Prepare a concise portfolio that showcases both code (GitHub) and visual results (e.g., safety detection screenshots).
- Be ready to discuss how you use Excel for large‑scale data exploration and how that fits into your ML workflow.
- Emphasize collaboration experience: describe times you worked directly with customers to refine model requirements.
- During interviews, articulate how you balance research rigor with production constraints in a fast‑moving environment.
- If offered a compensation package, ask about equity vesting schedule and remote‑work allowances before negotiating.
- Watch for vague promises about “flexible hours” without clear expectations on deliverables; seek clarity on communication cadence for remote teams.
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