Machine learning engineer

Perceptive Automata is a fast-growing machine learning and computer vision company started by Harvard and MIT scientists. We are using our transformative technology to help make life safer and happier for millions of people.  We're working with investors who have supported some of the fastest-growing tech companies in the world.

We are hiring an engineer to help develop our core technologies, algorithms and data collection pipeline.  As we are a small team, you will be expected to use a wide range of skills and be actively engaged in the long-term planning of our data collection and analysis strategy.  


  • Background in Machine Learning, either academic (PhD or Masters) or equivalent professional experience
  • Strong background in statistical inference
  • Experience using cloud-based and desktop tools for management of massive-scale data
  • Experience working in a team on large-scale, production-quality Python projects
  • Experience managing large-scale, heterogeneous data sets
  • Experience with state-of-the-art machine learning architectures such as LSTM, RNN or GAN


  • History of academic publications on machine learning theory or techniques
  • Experience building custom CNNs
  • Experience building databases and querying data in PostgreSQL 

  • Competitive compensation including benefits and equity
  • Company culture committed to sustainable performance with work/life balance
  • Lunch reimbursement
  • Guest lectures, learning opportunities with connections to labs at Harvard and elsewhere, and publication opportunities


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.