Data Platform Engineer Lead, EvolutionaryScale
Artificial Intelligence
$150-350k
+ Equity
Frontier AI models for biology
Job no longer available
Frontier AI models for biology
1-20 employees
Job no longer available
$150-350k
+ Equity
1-20 employees
Company mission
To develop artificial intelligence to understand biology for the benefit of human health and society.
Role
Who you are
- Senior-level engineer with 3+ years (ideally 5+) designing and scaling large-scale data infrastructure
- Deep experience with distributed data frameworks such as Spark, Ray, or Flink for large-volume, high-throughput processing
- Foundation in data platform concepts: metadata stores, lineage tracking, orchestration tools, schema evolution, dataset versioning
- Skilled in debugging, performance optimization, and building observability into data systems
- Collaborative mindset - you can partner effectively with scientists, ML engineers, and infrastructure teams
- Excited by the chance to define new standards for data infrastructure in a domain that could reshape medicine and biology
- Experience with major cloud providers (AWS, GCP, or Azure), including familiarity with data warehousing tools is a plus
- Knowledge of large-scale distributed systems, machine learning, biology and biology datasets is a plus
What the job involves
- As our Data Platform Lead Engineer, you'll own the architecture and execution of EvolutionaryScale's data platform - the backbone that powers training, evaluation, and discovery across our models
- You'll build reliable, scalable, and transparent pipelines that process biological data at unprecedented scale and ensure every dataset - pre-training or post-training - is high-quality, reproducible, and traceable
- You'll collaborate closely with bioinformatics, modeling, research and infrastructure teams to design systems that enable our scientists and modelers to move faster, experiment more effectively, and generate insight from massive biological data
- Architect and operate large-scale data processing pipelines (batch + streaming) for pre-and post-training biology datasets - covering raw sequence, structure, and model-generated data
- Build and evolve our data platform: data lakes/lakehouses, metadata and lineage systems, feature stores, and orchestration frameworks
- Define and implement data cataloging, governance, and versioning practices that ensure full reproducibility and traceability across datasets
- Collaborate with researchers and ML engineers to translate modeling requirements into robust data systems that optimize throughput, reliability, and cost
- Establish best practices for data CI/CD, observability, infrastructure-as-code, fault tolerance, and data quality monitoring
- Continuously explore and integrate emerging technologies - Ray, Spark, Flink, modern data mesh approaches - to keep our stack state-of-the-art
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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