Software Engineer, Data & ML

About Foray

Foray is a plant production company using plant cells, artificial intelligence, and advanced biomanufacturing to grow materials, molecules, and seeds directly from the cell up. By combining predictive AI/ML with in vitro plant biology, Foray helps unlock resilient crops, scalable seed systems, harvest-free plant products, and new forms of bioproduction across industries.

Our work is powered by Pando, Foray’s foundational workspace for plant science. With novel plant datasets and emerging predictive models, Pando helps researchers design and optimize plant production workflows with greater speed and reliability, making plant production more than 3x more successful and more than 3x faster. Together, Foray’s software and biomanufacturing platforms are creating new ways to produce what we need from plants while building more resilient plant industries.

About the Role

We’re looking for a mission-driven Software Engineer to help build the software and data foundation behind Pando. You’ll work across the product, from backend services and data systems to user-facing features. A major part of this role will be turning complex scientific and experimental information into reliable, useful data that can power both Pando and our machine learning systems.

We’re looking for a strong engineer who can reason through unfamiliar problems, learn quickly, and build thoughtful systems. You’ll work closely with software engineers, biologists, and machine learning researchers and have meaningful ownership over both what we build and how we build it. This is an opportunity to join early, work across disciplines, and help build an entirely new way of working with plants.

Responsibilities

• Build and ship production software across Pando, with a focus on backend systems, APIs, data infrastructure, and the systems that support user-facing product experiences

• Design and maintain how scientific and experimental data is ingested, structured, stored, versioned, accessed, and used across the organization

• Build workflows that turn complex and unstructured sources, including scientific literature and natural language, into reliable, structured data for product and machine learning applications

• Partner with scientists and machine learning researchers to translate experimental workflows, statistical analyses, and design-of-experiment approaches into scalable software, data systems, and predictive tools

• Establish strong practices around data quality, provenance, reproducibility, access management, and reliability as Foray’s scientific data and software systems scale

• Make thoughtful technical and architectural decisions, balancing speed, simplicity, scalability, and long-term maintainability as the platform evolves

You may thrive here if you

• Are a strong software engineering generalist with particular depth in backend and data systems. You don’t need to specialize in frontend, but you’re comfortable contributing to it and understand the broader product stack well enough to make informed technical decisions

• Have experience shipping production-grade software and designing backend systems, data pipelines, databases, APIs, or other data-intensive infrastructure

• Are familiar with MLOps and the infrastructure needed to run AI models in production

• Are strong in Python and comfortable working with relational databases, APIs, and modern software systems

• Are comfortable turning messy, heterogeneous, or unstructured information into trustworthy data, including through natural language processing, information extraction, or similar techniques

• Understand good scientific data practices, including quality, provenance, versioning, reproducibility, permissions, and access controls

• Have enough statistical fluency to reason about experimental data, uncertainty, and design of experiments and can work effectively with scientists and machine learning researchers

• Bring informed technical opinions without being dogmatic, learn unfamiliar domains quickly, and enjoy solving ambiguous problems with significant ownership

Experience with scientific or biological data, machine learning infrastructure, predictive modeling, optimization, or AI applications is helpful, but we don’t expect one person to arrive having done all of these things before.

Additional Details

• Must be authorized to work in the United States.

• Compensation Range: $105,000-$130,000, plus equity

• Location: On-Site in Greater Boston, Massachuestts

• How to apply: We take the time to read each application closely. Thoughtful, clear responses help us get to know you. Please apply via the Polymer form. Including links to your LinkedIn profile and GitHub is strongly encouraged.

Foray deeply values diversity and is committed to creating an inclusive environment for all employees. We are an equal opportunity employer. We consider all qualified applicants equally for employment. We do not discriminate on the basis of race, color, national origin, ancestry, citizenship status, protected veteran status, religion, physical or mental disability, marital status, sex, sexual orientation, gender identity or expression, age, or any other basis protected by law, ordinance, or regulation.