Staff Machine Learning Scientist

2 days ago

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Recursion

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Decoding Biology to Radically Improve Lives

Pharmaceuticals • Drug Discovery • Rare Diseases • Drug Repurposing • Inflammation

201 - 500

💰 $150M Post-IPO Equity on 2022-10

Description

• As a Staff Machine Learning Scientist, you will be contributing to dynamic short to medium term projects that derisk novel capabilities. • You will conceptualize and directly contribute to the development of novel ML models across a range of data types including vision, genomics, other Omics and clinical data. • By leveraging your experience in machine learning, drug discovery, software engineering, and data, you will: • Conceptualize and scope 3-6 month high impact projects for cross-functional workstreams • Directly contribute to and coordinate execution of these projects • Mentor other data and machine learning scientists • Interface with a diverse range of collaborators, including company leadership (VP+) • Work within dynamic, interdisciplinary teams of biologists, product managers, data and ML scientists, software engineers, and more • Build and curate large scale datasets for training machine learning models across multiple modalities • Develop new algorithms and architectures and train large models on these datasets • Explore properties of the resulting representation model on a range of benchmarks • Develop new benchmarks for interpreting how models are behaving • Work with other teams to support deploying these models to Recursion’s platform

Requirements

• Expert knowledge in machine learning theory & practice and its applications to challenges in biological or medical science including the ability to: • Ideate and scope net-new impactful ML-based projects that can impact drug discovery • Coordinate with stakeholders and teammates as well as contribute directly to execute on projects • Develop net-new algorithms and architectures, particularly leveraging self-supervised and multi-modal learning • Experience with one of but ideally multiple types of biological data (microscopy, histology, transcriptomics, clinical data) • Run quick and focused computational experiments evaluating project feasibility • Work closely with biologist to develop new training and benchmarking datasets • Interpret and develop benchmarks for assessing model performance • Tools: PyTorch, NumPy, Pandas, GCP, Hybrid Cloud, Linux, CUDA, Docker, Kubernetes, BigQuery, large scale distributed systems

Benefits

• You will join an interdisciplinary team that’s having a major impact internally and externally • You will contribute to conference publications and have the opportunity to attend major ML conferences • You will collaborate with other cutting edge teams at Recursion, including Valence Labs at Mila in Montreal