An innovative early-stage company working at the intersection of technology and clinical science is hiring a Python Software Developer to join a small, high-impact engineering team. This is a chance to see your work reach real users from day one. As Python Software Developer, you’ll take on full-stack responsibilities across front-end and back-end development, including integration with the company’s data pipeline. Day to day, you’ll build customer-facing features, improve dashboards and visualization tools, and contribute to machine learning initiatives such as boundary detection for cancer cell analysis. Expect to commit code on your first day and to ship something meaningful within 90 days, whether that’s a customer-facing feature or a laboratory workflow automation.
About the Company — Life Sciences Software for Clinical Workflows
Company Type: US-based early-stage life sciences technology company
Focus: Software supporting clinical trial workflows and laboratory processes
Team Size: Small by design, so each engineer has direct impact
Engineering Culture: Shipping quality products to real users
Offices: San Mateo, California, or Salt Lake City, Utah
Python Software Developer Role — Full-Stack & Scientific Data Engineering
Department: Software Engineering
Primary Focus: Full-stack development, data pipeline integration, dashboards
Scope: Customer features, visualization tools, machine learning initiatives
Mission: Building products that make a tangible difference to customers and outcomes
Python Software Developer Position Overview
The Python Software Developer role sits at the heart of a small engineering team building software for clinical and laboratory science. The work spans the full stack: you’ll build responsive front-end interfaces, develop back-end services in Python, and connect everything to the company’s data pipeline so that scientific information flows reliably to the people who need it. Customer-facing features are a priority, and you’ll also improve the dashboards and visualization tools that help researchers and clients make sense of complex results. Machine learning is part of the picture too, including boundary detection for cancer cell analysis, which requires careful thinking about data quality and model behavior. Because the team is small, your contributions will be visible quickly. The expectation is that you’ll be committing code from day one and shipping something meaningful within your first 90 days, whether that is a customer-facing initiative or a workflow automation that saves lab time. You’ll weigh when to build from scratch, when to reuse existing components, and when automation genuinely adds value, and you’ll explain those decisions clearly to non-technical colleagues and stakeholders.
As Python Software Developer, you’ll grow your expertise in cloud computing on GCP or AWS, deepen your skills in React and TypeScript, and gain hands-on experience with large and complex scientific datasets, including bioinformatics data where that background is a strong advantage. You’ll learn how software supports clinical trial workflows and laboratory processes, and you’ll see your work reach real users and shape real outcomes. The ideal candidate has strong Python skills, familiarity with at least one cloud platform, a track record of shipping software or strong internship experience from teams with high engineering standards, and the ability to communicate technical ideas clearly to people outside engineering. Experience with scientific data is essential, and a background in bioinformatics is a strong plus. For developers who want to build things that matter in life sciences, this role offers a rare combination of technical depth, product ownership, and direct impact.
Why This Role Matters: As Python Software Developer at this early-stage company, you help shape a product from the ground up, see your code reach clinical and laboratory users quickly, work across the full stack from dashboards to data pipelines, contribute to machine learning in cancer cell analysis, build a portfolio of meaningful shipped work within your first 90 days, and grow into a senior engineering career in life sciences technology.
Key Responsibilities & Engineering Duties
Full-Stack Development
- Build customer-facing features across front-end and back-end
- Develop services and tools in Python
- Build user interfaces using React and TypeScript
- Ship features that reach real users quickly
- Commit production-quality code from day one
- Deliver a meaningful release within the first 90 days
Data Pipeline Integration
- Integrate applications with the company data pipeline
- Handle large, complex scientific data sets
- Build reliable data flows for research and clinical users
- Improve data processing and quality checks
- Support bioinformatics and scientific data workflows
- Optimize performance across data-heavy systems
Dashboards & Visualization
- Improve dashboards for clients and internal teams
- Build visualization tools for complex results
- Make scientific data clear and actionable
- Iterate on interfaces based on user feedback
- Translate technical outputs into usable views
- Maintain consistent, accessible design across tools
Machine Learning Initiatives
- Contribute to machine learning development projects
- Support boundary detection for cancer cell analysis
- Evaluate model outputs with careful attention to data quality
- Integrate models into production workflows
- Collaborate with scientists on analytical requirements
- Assess when automation adds real value
Lab Workflow Automation
- Automate laboratory workflows where it saves time
- Support clinical trial workflow software
- Reduce manual steps in data handling
- Decide when to build, reuse, or automate
- Document processes for future maintenance
- Improve reliability of lab-facing tools
Cross-Team Communication
- Explain technical concepts to non-technical stakeholders
- Collaborate with scientists, product, and leadership
- Share progress and trade-offs clearly
- Contribute to a culture focused on shipping quality products
- Participate in design and code review discussions
- Keep team stakeholders informed on priorities
Qualifications & Requirements
Core Technical Skills
- Strong Python skills
- Familiarity with at least one cloud platform (GCP or AWS)
- Experience working with large, complex data sets
- Ability to ship software and deliver working features
Preferred Skills
- Exposure to React and TypeScript
- Background in scientific data or bioinformatics
- Strong internship experience from high-standard engineering teams
- Experience with machine learning applications
Professional Competencies
- Clear communication of technical concepts to non-technical audiences
- Practical mindset on building, reusing, and automating
- Ownership and bias toward shipping
- Comfort in a small, fast-moving engineering team
Career Development & Growth Opportunities
Professional Advancement
- Early-stage environment with high ownership and visibility
- Pathway toward senior software engineer or technical lead roles
- Opportunity to shape product architecture
- Exposure to both product and scientific leadership
Learning & Development
- Hands-on experience with cloud platforms
- Growth in full-stack development with React and Python
- Experience with clinical and laboratory software
- Exposure to machine learning in life sciences
About the Company — Technology Meets Clinical Science
This US-based early-stage company works at the intersection of technology and clinical science, building software that supports clinical trial workflows and laboratory processes. The team is intentionally small, which means every engineer’s work has a direct effect on customers and on outcomes. The engineering culture is centered on shipping quality products that reach real users, and the company offers flexibility to work from either its San Mateo or Salt Lake City office.
Career Excellence in Life Sciences Software: Join an early-stage team building products that matter, work across the full stack from data pipelines to dashboards, contribute to machine learning for cancer cell analysis, automate laboratory workflows, see your code reach users quickly, and grow a career at the intersection of software and clinical science.
Who Should Apply?
- Python Developers: Ready to build full-stack products
- Software Engineers: Looking for high-impact early-stage roles
- Data Engineers: Working with scientific or large datasets
- Bioinformatics Specialists: Moving into software engineering
- Recent Graduates and Interns: With strong shipping experience
- Full-Stack Developers: Interested in life sciences technology
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