Staff Machine Learning Engineer - Edge AI

United States Digital Space LLC; United States; Remote; USD 122,000 - 168,000; Full time

Benefits offered by this job

RSU grant

Job summary

the company AI team seeks a Staff Machine Learning Engineer to build end-to-end AI solutions for customers. You’ll work with ML engineers, scientists, and full-stack/firmware engineers to deliver core features and optimizations on edge devices.

You should apply if you want to impact global industries, scale with over 2.3 million IoT devices, and engage in continuous learning while collaborating with customers and product teams.

Qualifications

• 8+ years experience as a Machine Learning Engineer.
• Profound experience in optimizing ML models and systems for Edge compute constraints.
• Coding in Python or similar.
• Coding in C++ or Rust.
• Strong knowledge of end-to-end ML product development.
• Experience shipping production code at large scale.
• Ability to distill requirements into clear problems.

Responsibilities

• Lead design and implementation of critical AI product initiatives on Edge devices.
• Develop tactical AI solutions and long-term research.
• Work with petabyte-scale data including text, diagnostics, sensor, video and location data.
• Collaborate across business units to prototype AI experiences and optimize ML models for edge devices.
• Stay connected to research and adopt novel technologies.
• Promote the company’s cultural principles at scale.

Skills

Python

C++

Rust

Edge compute

ML engineering

Production code

Mentoring

Communication

Job description

Who we are

the company (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 the company, 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 the company 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 the company AI team builds end-to-end AI solutions for our customers as well as core ML infrastructure for the company. As a Staff Machine Learning Engineer, 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 ML Engineers and Scientists, as well as full-stack and firmware engineers to deliver core product features, services, and optimizations.

This is a remote position open to candidates residing in Canada. 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 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: the company 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 the company 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 on Edge devices.

• 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 and optimize the ML model performance on edge devices.

• Stay connected to industry and academic research and adopt novel technology that suits the company’s needs.

• Champion, role model, and embed the company’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:

• 8+ years experience as a Machine Learning Engineer.

• Profound experience in optimizing ML models and systems for Edge compute constraints.

• Coding in python or similar.

• Coding in C++ or Rust.

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

• Experienced in developing and shipping production code at large scale.

• 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 ML Engineers.

An ideal candidate also has:

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

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

• Deep knowledge in state of the art Computer Vision and multi-model models.

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

$170,400—$234,300 CAD

Total Rewards

At the company, 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 the company, 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 effectiv