What are the responsibilities and job description for the Software Engineer position at Blank Bio?
About Blank Bio
Blank Bio is an applied AI research lab focused on increasing the success rates of clinical trials. We do this by training RNA foundation models that learn the patterns that shape disease progression and patient response to treatment. We aim to help pharma make more informed decisions in clinical trials by capturing the biology that makes each patient’s tumour unique.
We’re a technical team of AI scientists and engineers from companies including Recursion, Deep Genomics, DeepMind, and Amazon, and institutions including Memorial Sloan Kettering Cancer Centre, Stanford, and the Vector Institute.
The Role
We are looking for a Software Engineer to own the engineering systems that hold our research and product surface together: benchmarking suites, containerization, internal tooling, partner-facing inference, and the reproducibility scaffolding that lets the rest of the team move fast without breaking things. You will work closely with our ML engineers and research scientists. As an early-stage startup, we move fast, work across disciplines, and embrace ambiguity. We’re looking for people who thrive in dynamic environments, are eager to take ownership, and want to help define both the science and the culture of the company.
Responsibilities
Must-haves
Blank Bio is an applied AI research lab focused on increasing the success rates of clinical trials. We do this by training RNA foundation models that learn the patterns that shape disease progression and patient response to treatment. We aim to help pharma make more informed decisions in clinical trials by capturing the biology that makes each patient’s tumour unique.
We’re a technical team of AI scientists and engineers from companies including Recursion, Deep Genomics, DeepMind, and Amazon, and institutions including Memorial Sloan Kettering Cancer Centre, Stanford, and the Vector Institute.
The Role
We are looking for a Software Engineer to own the engineering systems that hold our research and product surface together: benchmarking suites, containerization, internal tooling, partner-facing inference, and the reproducibility scaffolding that lets the rest of the team move fast without breaking things. You will work closely with our ML engineers and research scientists. As an early-stage startup, we move fast, work across disciplines, and embrace ambiguity. We’re looking for people who thrive in dynamic environments, are eager to take ownership, and want to help define both the science and the culture of the company.
Responsibilities
- Build and maintain our benchmarking infrastructure for evaluating models against the tasks that matter clinically.
- Containerize training, evaluation, and inference workloads so they run identically anywhere we ship them, including air-gapped partner environments.
- Build the data pipelines and internal tooling that scientists use day to day, from raw RNA-seq through preprocessing, QC, and result delivery.
- Build the inference services partners use to run our models against their own data.
Must-haves
- 3 years of experience shipping production systems
- Strong proficiency in Python
- Experience with Docker and container orchestration, including debugging complex or hard-to-reproduce build and deployment issues.
- Experience owning services end-to-end, from system design and implementation through deployment, monitoring, on-call support, and long-term maintenance.
- Experience building APIs or tools that make models accessible to other engineers, scientists, or customers
- Familiarity with transcriptomics, RNA biology, or other -omics data.
- Experience shipping software into regulated, security-sensitive, or air-gapped environments.
- Previous work in an early-stage, fast-paced environment.
- Competitive salary and meaningful early-stage equity.
- Comprehensive health, dental, and vision coverage.
- Generous vacation and parental leave policies.
Salary : $150,000 - $250,000