Machine Learning Engineer
At HyperScience, we use modern machine learning to turn documents into machine-readable data. Our customers receive a wide variety of documents, like life insurance applications, paystubs, utility bills, insurance claims, that must be processed quickly and accurately to better serve the people at these organizations, and their customers. Amazingly, this is all done manually today. We’re on a mission to change that!
Our product is already delivering value to large, blue-chip organizations in financial services and insurance, and we see a massive opportunity to expand to more industries and automate more business processes. We are looking for people who are excited to help us build upon this foundation and vision.
Founded in 2014 by Peter Brodsky, Vladimir Tzankov, and Krasimir Marinov, Hyperscience has raised $50 million from Third Kind, SV Angel, The Stripes Group, Firstmark, Battery Ventures, and Felicis Ventures.
We are focusing on understanding document images and extracting structured data. This naturally leads us to solve a number of problems in machine perception and natural language understanding. ML is at the core of what we do. We turn ML lab experiments into enterprise-ready AI solutions - and we’re looking for continuous learners to work on these efforts. This is an opportunity to work on the full lifecycle of an ML solution - you will research cutting edge techniques, implement them in a fast-growth AI startup environment, and ensure thеy are integrated in a reliable and scalable way to bring real value to customers. Furthermore, you’ll provide opportunities for these models to be automatically retrained and get smarter over time!
- Following AI/ML research. and apply it to create technologies for automating cumbersome business work like data entry.
- Bringing algorithms and models research into practice. Helping integrate the state of the art into HyperScience’s products.
- Owning ML models end-to-end, from collecting training data to deploying in production.
- Responsible for the quality and ongoing evaluation of the ML models
- Working closely with the application teams to successfully integrate models into our product.
- Collaborate with other engineers to build common tools for accelerating ML research internally.
- 2 years relevant professional experience
- Solid understanding of Math and CS fundamentals
- Strong analytical skills
- Knowledge of modern ML/DL technologies and experience applying them to real-world projects
- Experience in Computer Vision or NLP is a plus.
- Able to perform applied research projects and bring them to production.
- Experience with one or more general purpose languages (Java, C/C++, Python, etc)
- Demonstrated ability to write high-quality code is an advantage
- Team player with strong communication skills
Benefits & Perks
- Top notch healthcare for you and your family
- 30 days of paid leave annually to help nurture work-life symbiosis
- A 100% 401(k) match for up to 6% of your annual salary
- Stock Options
- Paid gym membership
- Pre-tax transportation and commuter benefits
- 6 month parental leave (or double salary to pay for your partner's unpaid leave)
- Free travel for any person accompanying a breastfeeding mother and her baby on a business trip
- A child care and education stipend up to $3,000 per month, per child, under the age of 21 for a maximum of $6,000 per month total
- Daily catered lunch, snacks, and drinks
- Budget to attend conferences, train, and further your education
- Relocation assistance
We are an equal opportunity employer. We welcome people of different backgrounds, experiences, abilities and perspectives. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. For Sofia:All job applications will be treated and processed with strict confidentiality and in full compliance with the GDPR provisions. 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 disability status.