Senior Machine Learning Engineer - Platform

About the role

We are looking for a Senior Machine Learning Engineer to lead the architectural evolution of our safety systems. You will move our ML stack from siloed, end-to-end models toward a unified Perception Platform Layer. Your mission is to build the robust infrastructure that translates raw sensor data into real-time, high-stakes decisions, ensuring our models perform reliably across both cloud and edge environments.

This is a remote position for candidates based in the US.

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 work on the following

1. Platform Architecture & Unification

• Architect a Unified Perception Layer: Lead the transition from fragmented, task-specific models to a modular perception platform that supports reusable components and downstream safety applications.
• System Design: Design and implement real-time ML systems—from sensor ingestion and tracking to risk reasoning and actuation—ensuring clear interfaces and predictable system behavior.
• Hybrid Deployment: Orchestrate model integration across edge and cloud environments, managing versioning, rollouts, and mission-critical fallback mechanisms.

2. Performance & Reliability Engineering

• Latency Ownership: Own end-to-end latency and reliability for safety-critical pipelines. You will profile, schedule, and optimize messaging and backpressure across the entire stack.
• Observability & Feedback Loops: Build sophisticated monitoring for deployed models to detect drift, false positives/negatives, and latency regressions. You will "close the loop" to ensure production data informs the next iteration of training.

3. Rigorous Evaluation & Safety

• Safety Cases: Develop evaluation frameworks specifically for rare "long-tail" safety events. You will define metrics and build targeted test sets that form the basis for principled ship/no-ship decisions.
• Explainability: Partner with Applied Scientists to ensure research outputs are translated into production code that is not only performant but also debuggable and explainable.

4. Technical Leadership

• Strategic Influence: Shape the system abstractions early in the platform transition to minimize technical debt and maximize future scalability.
• Mentorship: Set the engineering standard for correctness and performance. You will mentor junior and mid-level engineers, fostering a culture of rigorous ML engineering.

Minimum requirements for the role

• Experience: 6+ years of experience in ML Engineering, with a proven track record of shipping models in production (ideally in safety-critical domains like robotics, automotive, or industrial AI).
• Systems Mastery: Deep understanding of distributed systems, performance profiling, and computer vision.
• Infrastructure Fluency: Experience with Cloud ML workflows (AWS/GCP/Azure) and containerization, paired with an understanding of the constraints of edge hardware.
• Architectural Mindset: You don't just write code; you design systems. You understand the trade-offs between model complexity and operational reliability.

An ideal candidate also has

• Ph.D. in Computer Science or quantitative discipline (e.g., Applied Math, Physics, Statistics)
• Experience with containerization technologies (e.g., Docker, Kubernetes), continuous integration/continuous deployment (CI/CD) pipelines, and infrastructure-as-code (IaC) frameworks
• Familiar with deploying and managing ML applications in cloud environments, as well as leveraging cloud-based services for data storage, processing, and inference
• Experience building end-to-end ML applications from scratch

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.

Annual Base Salary$243,100—$286,000 USD

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.

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Fraudulent Employment Offers

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