Infrastructure Engineer
North America (Remote) /
Engineering – Infrastructure /
Full-Time Employee
/ Remote
Edge Impulse is the leading edge AI platform, enabling all enterprises to build smarter edge products. Our technology empowers developers to bring more machine learning products to market faster. Enterprise teams develop industry-specific solutions in weeks instead of years because of the powerful automation and low-code capabilities we provide. We believe that data-centric engineering is the future of industry transformation, unlocking a positive impact on our society and environment.
The Edge Impulse Infrastructure Engineering team builds scalable infrastructure that quickly transforms terabytes of customer data. We work hand in hand with our ML engineers to design systems to automatically find the best model architectures. We provide our community and customers with a rock-solid and scalable platform.
Edge Impulse is an engineering company providing the first fully integrated machine learning platform for smart and secure edge products. Our infrastructure engineers routinely work on problems in distributed computing, large-scale system design, networking and data storage, security, developer tooling, and more in order to serve more than 100,000 projects running on our platform.
Primary Responsibilities
- Keep infrastructure rock solid, making sure we can scale up automatically, and proactively monitoring for potential issues
- Work with the rest of the engineering team to design for scale
- Identify bottlenecks in our code base
- Maintain our internal infrastructure (thousands of integration tests that run on every commit, reports for user activity, and admin panels for our solutions engineers)
- Place observability at the center of our workflow
- Ensure cloud infrastructure meets security compliance standards (e.g. SOC2 and HIPAA)
- Iterate quickly on experimental new features to solve real user problems, and enable other engineers in the team to do so by offering high-quality CI/CD pipelines & integration tests
- Understand ML Ops and work alongside our ML and embedded teams to push the boundaries in embedded ML
Preferred Skills and Experience
- A minimum of five (5) years of experience developing large-scale infrastructure, distributed systems or networks, and/or experience with compute technologies, storage or hardware architecture
- Experience working on cloud IaaS, PaaS or SaaS products
- Strong experience using cloud platforms and/or containerized application deployments
- Production experience managing Kubernetes (K8s) clusters
- Experience creating and/or managing production infrastructure with Terraform for AWS
- Experience with keys, secrets, and certificate management and principles
- Proficient in one or more programming languages (TypeScript, Python a plus)
Academic Credentials
- Bachelor’s degree or equivalent practical experience
What We Offer
- Competitive pay, stock options, benefits, and time off
- A dynamic culture that sees work as one element in life (work-life balance)
- A team that’s engaged and inclusive yet global and diverse
$113,000 - $153,000 a year
We base our salary ranges from compensation research using both historic and real-time salary data sets. We have a reasonable estimate of the current salary range to be USD$133K-$153K + annual bonus + equity + benefits. This range reflects the minimum and maximum target for new hire salaries for this position in Texas.
Edge Impulse targets overall compensation at the 75th quartile of the market for similarly placed companies, job families, and grade levels. Our salary ranges take into account a wide range of factors including but not limited to role, grade level, location, training, degrees, certifications, and other business needs.
We are an equal opportunity employer. We appreciate diversity in our remote, global organization. We value inclusivity across our teams. We encourage applicants of all genders to apply for this position. We do not discriminate against any employee or applicant for employment because of race, religion, color, national origin, gender identity, sex, sexual orientation, age, marital status, veteran status, disability status, or any other federal, state, or local protected class.
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