Senior Machine Learning Engineer

London, England /
Machine Learning – Machine Learning Engineers /
Full-time
Company Description
Hyperscience modernizes mission-critical processes and operations for the world's largest organizations and government agencies. Since 2014, Hyperscience’s automation technology has helped data-centric companies parse through vast amounts of unstructured inputs and raw information to get to swifter and smarter business outcomes. Through the Hyperscience Platform, enterprises are empowered to transform their operations, and drive operational efficiency as well as human productivity by fully unlocking the power of their data.

Ranked on the Inc. Fastest-Growing Company List, Hyperscience has raised $190M from investors including Tiger Global, BOND, Bessemer Venture Partners, Stripes, and FirstMark. The company has consistently been recognized as one of the best places to work with a collaborative and innovative culture and best-in-class benefits.

The company has a global footprint with offices in New York City, Sofia, Bulgaria, Toronto, Canada, and London, UK.

Job description:

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.

Responsibilities:

    • 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
    • Collaborating with other engineers to build common tools for accelerating ML research internally

Qualifications & experience:

    • Minimum 5 years of experience in Software Engineering, of which at least two in Machine Learning
    • Solid understanding of Math and CS fundamentals
    • Strong analytical skills
    • Practical experience  in modern ML/DL technologies (applying ML to real-world projects) 
    • Experience in Natural Language Processing 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.)
    • Professional experience with Tensorflow/Pytorch or other popular ML framework
    • Demonstrated ability to write high-quality code 
    • Team player with strong communication skills
    • Proficiency in written and spoken English language
Benefits & Perks:
- Top notch healthcare for you and your family
- 30 days of paid leave annually to help nurture work-life symbiosis
- Stock options
- Paid gym membership
- 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 dependent care and education stipend
- 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.