Director of Machine Learning Research
New York City - NY, Sofia - Bulgaria, Remote /
Hyperscience is a technology company blazing a new path in enterprise automation with a reimagined approach to building and powering processes. The Hyperscience Platform is the world's first Software-Defined, Input-to-Outcome Automation platform used by top public companies and government organizations around the world to build and run mission-critical processes with ease and speed.
Hyperscience helps enterprises quickly build and roll out new business processes with built-in automations, reduce manual errors, increase high- and low-skilled employee productivity, and eliminate the need for costly transformation. Hyperscience’s Intelligent Document Processing solution has been implemented at some of the world's leading financial services, insurance, healthcare and government organizations, including TD Ameritrade, QBE Insurance Group Limited and Voya Financial, helping them lower costs, reduce error rates by 67% and increase employee capacity by 10x.
Since its founding in 2014, Hyperscience has grown to more than 150 employees with offices in New York City, Sofia, Bulgaria, and London, UK, and has consistently been recognized as one of the best places to work, with a collaborative and innovative culture and best-in-class benefits.
Hyperscience is the world's first Software-Defined Automation Platform, used by top enterprise companies and government organizations to build and run mission-critical processes with ease and speed.
By enabling seamless human-machine collaboration, Hyperscience empowers its customers to tackle their trickiest problems: how to build processes that nimbly adapt to business needs, how to organize talent efficiently and effectively, and ultimately how to become performance-driven organizations with superior outcomes.
At Hyperscience, we are on a mission to redefine the future of work. The Hyperscience Platform is used by customers including TD Ameritrade, the VA (Veterans Administration), and others in the insurance, healthcare, financial services, legal, and public sectors. Our automation solution enables customers to lower their costs, reduce error rates by 67%, and increase employee capacity by 10x - and we’re just getting started.
We’re looking for amazing Machine Learning talent to join us on our mission to reinvent the way businesses and humans interact. Machine Learning sits at the core of our efforts to automate the future of work by creating a new digital assembly line, where humans and machines constantly interact and collaborate on mission-critical processes.
We are focused on building the world’s first Software-Defined, Input-to-Outcome platform by understanding documents, extracting structured and unstructured data, and automating business processes end-to-end - and we’re looking for amazing people to join us.
Machine Learning (ML) sits at the core of our efforts to automate the future work. We turn ML lab experiments into enterprise-ready AI solutions to solve complex machine perception and natural language understanding problems.
This is an opportunity to work on the full lifecycle of an AI solution - you will research cutting-edge techniques (Computer Vision, Natural Language Processing, Meta Learning, Online Learning), 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.
The Director of Machine Learning Research will lead a cutting-edge ML research team at Hyperscience. You will drive and lead mission-critical research and experimentation into new ML models and approaches. As a machine learning thought leader with a strong academic background in ML and AI, you will identify key strategic opportunities and areas for focused research, solidifying Hyperscience’s position as the leader in automation.
- Lead research into the latest ML academic literature in order to develop innovative new ML models and approaches, in areas such as on-premise learning and natural language processing.
- Lead a team that continuously adopts, experiments with and implements the latest ML research in order to develop new ML models and approaches.
- Leverage your ML industry expertise to introduce new technologies and processes to Hyperscience’s product offerings.
- Published researcher with a strong track record of academic experience in ML and AI.
- Deep technical background in applied machine learning, including deep learning, computer vision, natural language processing, and data engineering.
- Industry experience productizing ML insights
- Nice-to-have: Previous experience in building and leading ML teams in creating end-to-end machine learning pipelines, including algorithms and tooling.
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/UK roles: 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.