Full Stack Engineer
Perceptive Automata is a fast-growing machine learning and computer vision company started by Harvard and MIT scientists that is developing a novel approach to help make autonomous vehicles safer for others on (or near) the road. In the coming year, we’re anticipating rapid growth to support an increasing demand for this technology (we're working with Silicon Valley investors who have supported some of the fastest-growing tech companies in the world).
We are hiring a full stack engineer to help develop and maintain our data collection, aggregation, and annotation pipeline. As a member of our small team, you will be expected to use a wide range of skills and be actively engaged in the long-term planning of the collection and analysis of data that is used to train and validate our machine learning models.
strongly preferred skills and background
- B.S. in computer science or equivalent practical experience
- 2-5 years experience with full-stack web development
- Strong Python programming skills
- Experience with relational databases (we use PostgreSQL) and familiarity with data architecture for large-scale, resource-intensive data applications
- Amazon Web Services, including EC2, S3, and RDS
- Flask web framework
- Experimental psychology, cognitive science or neuroscience
- Competitive compensation including benefits and equity
- Company culture committed to sustainable performance with work/life balance
- Guest lectures, learning opportunities with connections to labs at Harvard and elsewhere, and publication opportunities
- Lunch reimbursement
PLEASE SUBMIT YOUR RESUME TO JOBS@PERCEPTIVEAUTOMATA.COM.
Are you an experienced programmer with extensive experience in developing real-time software products, but you don’t see yourself above? Get in touch! We’re a growing business and always looking for quality candidates that don’t fit easily into the boxes we envision.
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or ability status.