Principal AI Engineer - Edge AI Face Recognition
Xailient
Software Engineering, Data Science
About the Company
Xailient’s breakthrough technology dramatically reduces the costs of using Computer Vision AI in real-world applications. By reducing costs, we are accelerating the next wave of technology, bringing AI to the Edge for smart sensors and devices.
We are on our way to installing our edge software on 50 billion devices and we need your help!
Xailient is a revenue-producing, VC-funded start-up.
The Role in General
Xailient works with innovators and early adopter customers in the Edge computing space. We are seeking a Principal AI Engineer. This is a new role, and we expect you to put your own imprint on it.
This is a technical leadership role in a small, growing company, and with a requirement for significant hands-on development involvement. Leadership responsibilities will span from day-to-day technical management to macro-scale technology and team strategy. The right candidate will be ready (eager) to roll up your sleeves.
As a Principal AI Engineer you will play a critical role in the development of computer vision AI solutions for deployment at the edge of Internet-of-things (IOT) networks. The Principal will lead in defining and driving solution development for a range of AI problems and guiding the business as a technical subject matter expert.
This is an AI Engineering role, not an AI Science role. You and the team will be responsible for producing a diversity of AI models addressing an array of customers’ practical needs. This will entail trade-offs between generalizability, accuracy, memory, speed, and other performance characteristics. You’ll be working with product and customer timelines and quality criteria. Welcome to the leading edge of AI!
We embrace diversity. Part-time or full-time candidates will be considered. We welcome candidates with family/life commitments and part-time availability, but “full-time professional passion”.
This role is remote, and you are free to work from anywhere. The team is global and therefore early / late calls one or two times a week are common, for coordination / collaboration.
Everyone’s time is valuable so please help by only applying if you meet the Mandatory Requirements for this role - thank you.
Mandatory Requirements
- 7+ years of experience with Edge AI and Face Recognition
- Development and deployment of Face Recognition solutions in commercial setting.
- Experience developing custom deep learning computer vision AI solutions focused on face recognition and object detection.
- Experience deploying deep learning models for embedded devices / IoT edge devices, down to the chip level
- Demonstrated ability to go deep technically on AI methodologies that are best suited to specific business and customer problems, as well as elevate your thinking to consider business and strategic implications.
- Proven track record in developing AI solutions from 'concept to deployment'
- Experience with the MLOps processes, including lifecycle management and automation
- Degree-qualified in AI / Machine Learning / Computer Science or equivalent experience.
- Ability to work independently
- Experience mentoring, guiding, and leading other AI engineers
Responsibilities
- Lead research and development efforts on Face Recognition systems for Edge AI Devices.
- Monitor existing Face Recognition AI product performance and provide subject matter expert for further development / improvement.
- Stay current on the latest cloud / edge AI/ML technologies, trends, and methodologies.
- Lead research effort to explore the latest cloud / edge AI models and methodologies that can be applied on existing or new edge AI product development.
- Provide subject matter expert input on business engagements and product road maps
- Design and develop robust AI solutions using commercial and custom deep learning AI tools.
- Review and approval of work performed by others
- Capability development across AI-related aspects of Xailient business/engineering/operations
Technical Skills / Experience
- Strong fundamental understanding on how face recognition and object detection is trained. The candidate must have experience in modifying model architecture, backbone and loss function to solve problems, e.g. speed, size, accuracy. Simply using an open-source model as-is would not be sufficient.
- Keeping abreast of the AI landscape and the latest academic papers and determining how we can apply leading edge concepts into our solutions
- Strong technical analytic skills in troubleshooting and experimentation to understand why a model behaviour and formulate fixes for any undesirable behaviour / performance.
- The ability to select an appropriate technical solution, utilizing benchmark data, and establishing sound tradeoff decisions regarding model behaviour and performance.
- Proficient with multiple deep learning frameworks such as TensorFlow, Keras and PyTorch
- Proficient in Python, C++ is highly regarded.
- Demonstrated ability to articulate AI-specific challenges and identify gaps.
- Excellent communication, written and verbal skills, to articulate challenging technical concepts to both lay and expert audiences
- Strong fundamentals in mathematics, computer science, information theory, probability, especially linear algebra
- Experience with AWS highly regarded
Non-Technical Attributes
- Customer Focus - Desire to deliver products that delight
- Communication - Explain technical topics to lay audiences
- Team Builder - We’re growing!
- Dependability - Deliver on promises, provide status proactively
- Initiative - see a problem, solve a problem
- Care for Quality - Care about your work and take pride in doing a good job
- Flexibility - Excited to learn new things and work outside of the comfort zone, comfortable with changing priorities of a startup environment
- Collaboration - Good ideas come from anywhere, great ideas come from collaboration
- Creative Problem Solver - turn abstract or vague ideas into actionable objectives
- Teamwork - No brilliant jerks, but weirdos welcome
