Software Engineer, EvolutionaryScale

Data Infrastructure

Salary not provided

AWS

GCP

Kafka

Hadoop

Azure

Spark

Flink

Senior and Expert level

New York

San Francisco Bay Area

Frontier AI models for biology

Be an early applicant

Frontier AI models for biology

1-20 employees

HealthcareB2BArtificial IntelligenceBiologySaaSScience

Be an early applicant

Salary not provided

AWS

GCP

Kafka

Hadoop

Azure

Spark

Flink

Senior and Expert level

New York

San Francisco Bay Area

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

Staff level engineers with 5+ years experience highly preferred
Proven experience with large-scale data processing systems using technologies such as Hadoop, Spark, or Ray
Knowledge of streaming data frameworks like Kafka Streams, Spark Streaming, or Flink
Understanding of data processing principles and best practices
Strong problem-solving skills, including the ability to research, debug, and resolve complex technical problems
Experience with major cloud providers (AWS, GCP, or Azure), including familiarity with data warehousing tools is a plus
Knowledge of biology and biology datasets is a big plus but not required
Experience with large scale distributed systems or machine learning is also not required but a plus

What the job involves

As a Data Infrastructure Engineer, you will work closely with bioinformatics and research teams to ensure our data jobs are reliable, efficient, and scalable
You'll implement best practices for handling large-scale data processing, select and integrate the right technologies, and drive continuous improvements in performance and quality of our data sets
Design, develop, and maintain large-scale batch processing pipelines using tools like Spark and Ray, for acquiring biology datasets
Manage data infrastructure components to ensure robust and fault-tolerant operations
Optimize data ingestion, storage, and retrieval processes for acquiring large and growing biology datasets, and for efficient pre and post training data ingestion
Create systems for easy and reproducible data evaluation and experiments
Integrate modern ML based data curation technologies with data processing pipelines
Work with researchers and other engineering teams to understand data needs, create solutions that meet modeling requirements

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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