Field Systems Engineer
Location: US, preference for Michigan or Eastern/Central US (must be authorized to reside and work in the US)
To apply, please email your resume.
Akridata is a US based startup founded in 2018 to build an edge data platform for the autonomous world.
Rich data in large volumes is being collected at the edge (outside a data center) in use cases like autonomous vehicles, smart manufacturing, satellite imagery, smart retail, smart agriculture, etc.
These datasets are characterized by being unstructured (images/videos), large size (Petabytes per month), distributed (across edge, on-prem and cloud) and form the input for training AI models to get to higher degrees of automation.
Akridata is engaged with building products that solve these unique challenges and is at the forefront of this edge data revolution.
The company is backed by prominent VCs and is actively recruiting in a number of areas.
Akridata is looking for a positive, can-do technical specialist to own pre-sales product demonstrations and solutions architecture, and provide post-sales support during deployment at key customers. Akridata supplies increasingly-critical edge-to-cloud infrastructure supporting perception training and automated driving development teams. If companies are collecting large amounts of camera/lidar/radar data, then they need help extracting features and cataloging the information in support of AI/ML development teams.
This is an individual contributor role with an opportunity to grow into a team leader.
Positive characteristics of a Field Systems Engineer
We are a sophisticated, high-performance team and are looking for high-capability people who are highly responsive.
Natural propensity to organize customer engagements and communicate effectively, externally and internally.
We respect each other to do-what-it-takes to build success which provides each of us with schedule flexibility motivated by an ever-present strong work ethic.
Understands that the customer, Product Development, Sales and Support are all working together toward the shared goal of customer success. A running project is the first sign of success, but how we get there is equally important.
As part of the solid communication, willingness to document software and processes to drive customer enablement and success.
- Minimum 3-4 years of Solution Engineering/Systems Engineering/Sales Engineering experience
- Ability to understand customer requirements and create customized demonstrations and collateral
- Provide product feedback (feature requests, user experience) to the development team
- Strong foundation in system level architectures and compute, storage and networking infrastructure, specifically:
- Compute architectures – physical and virtualized, operating systems (Linux strongly preferred)
- Storage systems – file systems, object stores
- On-prem data center and public cloud (AWS, Azure, Google Cloud) environments
Hands-on experience with Linux/Unix systems as a system administrator or equivalent role involving installing software and security patches, installing hardware components on servers as per product manuals etc.
Hands-on experience working with Linux command line tools.
Basic understanding of enterprise system deployment architecture around network configuration, security related settings etc.
Experience troubleshooting configuration issues to resolve them independently or in collaboration with customer support teams.
Be able to work with development/L3 support teams to live debug any issues for swift resolution
- Experience with programming or scripting languages such as Python, java, C++
Good to have
- Experience with data management, DevOps, micro-services, containerization
- Knowledge of Automotive systems and software standards e.g. AutoSAR, ISO 26262, ASPICE, etc.
A bachelor’s degree in Computer Science, Physics, Engineering, Mathematics, or another relevant quantitative field. Additional work experience is required for non-CS/IT graduates.
Helpful to have:
Understanding of the mathematical theory behind machine learning techniques for dimensionality reduction, clustering, classification, regression, and deep neural networks.
1+ years of experience in machine learning, or 2+ years of experience in data analysis.
We are searching for a high-capability person with hustle, intellect, and finish-the-job characteristics.