About Becoming

Becoming is building Developmental Intelligence: AI for predicting how organisms change over time.

Most experimental systems fail when metabolic demands become too high. We are building systems that don’t — by combining engineered metabolic environments, sensing, control, and software into tightly integrated products that operate reliably over long time horizons.

Hardware is core to our platform. It must work continuously, predictably, and under real biological constraints.

The Role

We are hiring a Bioinformatics Engineer to design and own data systems that translate high-dimensional biological measurements into structured, usable intelligence.

This is not a support analyst role. You will build computational pipelines and data architectures that integrate directly into Becoming’s predictive models and experimental platform.

You will operate at the interface of wet lab biology, machine learning, and systems engineering. You will define data standards, build scalable pipelines, and take responsibility for signal integrity from raw measurement to model-ready representation.

High agency is required. You will identify bottlenecks, design infrastructure, and own outcomes.

What You’ll Own

• End-to-end ownership of biological data pipelines
• Processing and QC of high-dimensional datasets (e.g., transcriptomic, imaging-derived, or multi-modal data)
• Scalable workflows for ingestion, normalization, annotation, and versioning
• Data models that support predictive and longitudinal analysis
• Integration of experimental metadata with biological readouts
• Reproducible computational infrastructure (cloud or on-prem)
• Validation frameworks for data integrity and drift detection
• Documentation and standards that enable scaling across teams
  

Who You Are

You are someone who:

• Operates with high agency — you identify problems, define solutions, and execute
• Takes end-to-end ownership of what you build
• Brings high energy to complex, ambiguous engineering challenges
• Acts with high integrity — you are honest about tradeoffs, risks, and failure modes
• Communicates directly and clearly, especially when something won’t work
• Is self-aware about your strengths and gaps, and proactively fills them
• Thinks like a systems integrator, not a narrow specialist
• Cares deeply about understanding systems at a first-principles level
  

• Degree in bioinformatics, computational biology, computer science, or equivalent demonstrated depth
• Experience building and maintaining biological data pipelines
• Strong programming skills (e.g., Python)
• Experience working with high-dimensional biological datasets
• Familiarity with version control, containerization, and reproducible workflows
• Demonstrated ability to turn ambiguous biological questions into structured computational outputs
• Comfort operating without heavy pre-built platform abstraction
  
  

Strong Signals

• Experience integrating multi-modal datasets
• Experience designing data systems for predictive modeling
• Work on longitudinal or time-series biological data
• Infrastructure-first mindset rather than analysis-first mindset
• Bias toward robustness and reproducibility

• Competitive salary and meaningful equity
• Full benefits
• High-trust, high-ownership environment
• Rapid growth in scope and responsibility