Applied AI Engineer
At Augustus we seek to provide intelligent, decision-making systems where others cannot. This calls for accelerating existing and state-of-art AI & ML towards production systems, while innovating in novel, creative ways. For the team at Augustus to be successful, we develop fundamental advances in AI, and repeatedly turn breakthrough technology ideas into products towards solving real-world problems with massive impact. At Augustus we’ve built a values-based culture for each individual member to accomplish their life’s best work.
As an Applied AI Engineer on the Augustus team, you will be responsible for developing, testing, and deploying AI/ML systems for our worldwide customer base. You will drive the acceleration of research projects -- from computer vision to NLP -- into production-quality, robust systems. The Applied AI team additionally runs rapid-prototyping sprints, pushing the boundaries of what is feasible and building unparalleled value for our customers. In fact, you play a critical role in delivering AI solutions that our customers haven’t even thought possible.
Your day will look a little something like this:
- Coding and coffee above the NYC skyline, at the top of the World Trade Center
- A mid-morning stand-up with the development team
- Quick sync with the Product-X working group (cross-functional units of designers, engineers, product managers, and researchers)
- Lunch with some teammates
- Put the finishing touches on an NLP demo
- Sit in on an AI journal club, learning about a new vision-as-inverse-graphics model
- Spend some uninterrupted quality time writing code, turning those red tests green
- 2+ years of non-internship professional software development experience
- Strong programming experience with Python and/or C++
- 1+ years of experience contributing to the architecture and design (architecture, design patterns, reliability, and scaling) of new and current systems.
- Experience communicating complex topics in a simple, understandable way
- Experience with a variety of machine learning methods and domains (namely computer vision and NLP)
- Experience in applying data science methods to business problems
- Computer Science fundamentals in data structures, algorithm design, problem solving, and complexity analysis
- MSc or PhD level in the field of Computer Science, Machine Learning, Applied Statistics, Mathematics
- Experience building complex software or data-driven systems that have been successfully shipped
- Knowledge of professional software engineering practices and best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
- Ability to take a project from scoping requirements through actual launch
- Experience in communicating with users, other technical teams, and management to collect requirements, describe software product features, and technical designs
- Experience across many areas of machine learning – Bayesian methods, deep learning, optimization algorithms, etc.
- Ability to rapid prototype AI/ML solutions, delivering proof-of-concepts with thorough project plans/estimates
Everyone on the Augustus team strives for these core qualities:
- Integrity, altruism, ability to admit when wrong
- Fearlessness, working outside your comfort zone
- Patience with others, and a sense of humor :)
- Fast worker and learner
- Intellectual breadth, and desire to grow
- Excellent communication skills and ability to work with people of various backgrounds
- Passionate about artificial intelligence, and pushing the boundaries on what humans can achieve with intelligent technologies
Augustus is proud to be an equal opportunity employer and prohibits discrimination and harassment of any kind. Our employment decisions are made solely on the basis of qualifications, merit, and business need, without regard to race, color, religion, family or parental status, sex or sexual orientation, gender identity, national origin, veteran or disability status, and age. We are committed to achieving a diverse workforce and encourage people of all backgrounds and identities to apply.