AI/ML Job: Machine Learning Engineer

BenevolentAI

Machine Learning Engineer at BenevolentAI

๐Ÿ‡บ๐Ÿ‡ธ United States โ€บ New York โ€บ NYC
  (Posted Jan 19 2021)

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About the company
The Company
BenevolentAI unites technology with human intelligence to re-engineer drug discovery and deliver life-changing medicines. We have developed the Benevolent Platformยฎ, a drug discovery platform built on powerful data foundations with state of the art machine learning and AI technology. Our technology empowers scientists to decipher the vast and complex code underlying human biology, find new ways to treat disease and personalise medicines to patients. Benevolent has active in-house R&D drug programmes in disease areas such as neurodegeneration, immunology, oncology and inflammation and has research and commercial collaborations with leading pharmaceutical and research organisations. The company is headquartered in London with a research facility in Cambridge (UK) and a further office in New York.
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Who we are
We are an eclectic bunch at Benevolent, united by our belief that innovative thinking and purposeful technology can truly change outcomes for the better. Our mission is to re-engineer drug discovery and deliver life-changing medicines for patients in need and we do this by applying AI, machine learning and other advanced technologies to reinvent the ways drugs are discovered and developed. We strive to bring together unique skills and perspectives across biology, chemistry, engineering, AI research, informatics, precision medicine and drug discovery.

Job description
The Machine Learning Engineering team is an interdisciplinary group focused on applying engineering rigour to machine learning problems on the BenevolentAI software platform. To carry out our role, we understand discoveries in machine learning algorithms, as well as the impact of a well-engineered model training and deployment infrastructure with a reliable data pipeline - and innovate on all.

Primary Responsibilities
Design and build software for machine learning applications to solve user needs across biology, chemistry, AI, and data science.
Promote machine learning best practices, such as: scalable training and deployment, model introspection and evaluation, new state-of-the-art implementations, etc.
Promote engineering best practices, such as: code reviews, test-driven development, pair programming, etc.

Additional Responsibilities
As a member of the Engineering team, you will be responsible for helping to define new directions and scope for existing and new software.
As a member of the Target Identification product team, you will be interfacing with users including Drug Discoverers and Bioinformaticians.

We are looking for someone with
Degree in Computer Science, Machine Learning, Artificial Intelligence (BSc/MSc/PhD) or related academic discipline.
Strong in at least one programming language (Python preferred).
Basic algorithms and data structures for software development.
Knowledge of modern tools for ML such as Tensorflow, Pytorch, etc.
Experience in implementing machine learning workflows.
Awareness and passion for the state-of-the-art in machine learning.
Understanding of distributed systems and microservice architectures.
Experience developing at least one of the following software systems: databases, APIs, microservice architectures, web frameworks, core machine learning libraries.
Experience in at least one of the following software domains: frontend development, backend development, data processing pipelines.

Nice to haves
Basic knowledge of biology, and/or experience working with biomedical data.
Knowledge of the pharmaceutical industry, ideally with a focus on drug discovery.

Together, we envision a world in which no disease goes untreated. If you are benevolent, curious, want to tackle real world problems and are willing to embrace new ideas, hit that โ€˜applyโ€™ button and join us.

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Company: BenevolentAI

BenevolentAI
job info / career page
Linkedin profile
Location: NYC, New York, United States

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Skills wanted for this job:
ai ml python pytorch tensorflow

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