Machine Learning Engineer, EvolutionaryScale

$150-350k

AWS

Docker

Kubernetes

GCP

Azure

Spark

Pandas

PyTorch

Junior, Mid and Senior level

New York

San Francisco Bay Area

More information about location

3 days a week in office

Frontier AI models for biology

Open for applications

Frontier AI models for biology

1-20 employees

HealthcareB2BArtificial IntelligenceBiologySaaSScience

Open for applications

$150-350k

AWS

Docker

Kubernetes

GCP

Azure

Spark

Pandas

PyTorch

Junior, Mid and Senior level

New York

San Francisco Bay Area

More information about location

3 days a week in office

1-20 employees

HealthcareB2BArtificial IntelligenceBiologySaaSScience

Company mission

To develop artificial intelligence to understand biology for the benefit of human health and society.

Job

Company

Role

Who you are

Experience with Pytorch or low-level programming is a plus
Experience with distributed computing frameworks like Apache Spark or Dask
Knowledge of cloud computing platforms like AWS, Google Cloud, or Azure
Familiarity with containerization and orchestration tools such as Docker and Kubernetes

What the job involves

Contribute to the process of transitioning research to product by deploying models to production environments
Collaborate with researchers and engineers at the company’s partners (clients or academic partners) to deploy the company’s technology within their infrastructure. Be effective representatives of the company and our products to partners and other external collaborators
Manage artifact tracking for different fine-tuned models and data
Conduct data pipeline work including use of Apache Spark, Apache Arrow, Pandas, distributed computing for large-scale data processing
Help cultivate best practices in MLOps, and think about the full ML lifecycle, including data, fine-tuning, deployment, reliability and monitoring
Work on simplification and improvement of codebase abstractions to accelerate research momentum
Possess the ability to execute complex modifications to the research pipeline, such as fast data loading and distributed training
Handle DevOps responsibilities, focused on making all engineers and researchers more productive. This includes tasks like cluster monitoring, unit testing and integration testing of research codebase, and continuous integration

Our take

EvolutionaryScale, an AI startup pioneering the 'ChatGPT moment for biology', is at the forefront of transforming the field with its ground-breaking technology. Backed by Amazon Web Services and NVIDIA's venture capital arm, the company aims to revolutionize biology through artificial intelligence.

Central to EvolutionaryScale's mission is ESM3, the first large language model for creating novel proteins. It leverages a vast dataset of nearly 2.8 billion proteins, plus computational tools that analyze protein sequence, structure and function simultaneously. This can help accelerate drug discovery, as well as enable sustainable solutions through engineered microbes.

EvolutionaryScale's approach should help accelerate scientific breakthroughs and enhance precision in biotechnological applications. The company's success hinges on its ethical use of AI to tackle these challenges, by accelerating protein engineering beyond natural evolution so that it can be put to use against our greatest problems.

Steph

Company Specialist at Welcome to the Jungle

Company

Funding (1 round)

Jun 2024

$142m

SEED

Total funding: $142m

Company HQ

Civic Center, New York, NY

Leadership

Alex Rives

(Co-Founder)

Serial Entrepreneur having previously co-founded Kallyope, Syros Pharmaceuticals and Fate Therapeutics. Before founding Evolutionary Scale they worked as a Research Scientist at Facebook AI.

Tom Sercu

(Co-Founder)

Previously an Engineering Manager at Meta. Before that they were a Research Engineer at IBM and a Research and Teaching Assistant at New York University.

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