Staff Engineer, Machine Learning Life Sciences

## Staff Engineer, Machine Learning Life Sciences Apply locations:
Cambridge, MAtime type:
Full time posted on:
Posted 6 Days Agojob requisition :
R-100071
** About Inari...
** Inari is the SEEDesignTM company. We embrace the diversity and complexity of nature in every aspect of our business to drive innovation – to push the boundaries of what is possible. Through our unrivaled technology platform, Inari uses predictive design and advanced multiplex gene editing to develop step-change products. We are taking a nature positive approach to unlock the full potential of seeds that will transform the food system.

The results will lead to more productive acres delivering value creation for farmers and a more sustainable future for our planet.
** Our success is dependent on great minds, collaborating to generate bright ideas and deliver exceptional outcomes.
** We have 200 employees, with research sites in Cambridge, MA (USA) and Ghent (Belgium), as well as a product development site in West Lafayette, IN (USA). We’ve deliberately built a team that brings diversity of thought to all aspects of our business, to generate new ideas, approaches, and ways of operating. And we've intentionally combined experience with potential, bringing agriculture industry experts with the desire to innovate together with bright minds from academia, human therapeutics, software, and consulting.

If you want to be part of a diverse and inclusive team developing unique solutions to feed the world while protecting our planet’s natural resources, we’d love to hear from you!
** About the role...
** Inari is seeking a Staff Machine Learning Engineer to join our AI Team in support of our mission of transforming agriculture through predictive design and advanced gene editing. This role will focus on delivering production-ready ML pipelines using existing models while also exploring new modeling approaches to advance our ability to drive step-change trait improvement in  this role, you will bring established best practices for building, deploying, and maintaining ML systems, and effectively apply that expertise in a life sciences context.

While life science experience is not a requirement, you are comfortable — or willing to become comfortable — working alongside biologists and reasoning about biological data.

As a staff-level individual contributor, you will drive major work streams with autonomy while collaborating closely with cross-functional teams of computational biologists, software engineers, and crop scientists.

This role is based in our Cambridge, MA office and follows our flexible hybrid work model, with time on a weekly basis split between in-office and remote work.
** As a Staff ML Engineer, Life Sciences you will...
*** Build, deploy, and maintain production ML pipelines and infrastructure to serve predictions at scale, including model versioning, monitoring, and lifecycle management
* Integrate ML systems with genomic, phenotypic, and biological data platforms using AWS and containerization technologies
* Partner with computational and experimental biologists to contextualize heterogeneous biological data and drive research-critical modeling programs
* Train and validate statistical and ML models; prototype new approaches and evaluate feasibility for production deployment
* Implement integrations with strategic third-party tools, foundation models, and AI agents; stay current with ML research to identify applicable methods
* Drive major work streams autonomously while collaborating effectively with teammates and cross-functional stakeholders
* Communicate technical results clearly across disciplines and contribute to technical decisions, code reviews, and engineering standards
** You Bring...
** Required
* *
* Education & experience:

** MS or PhD in Computer Science, Engineering, Statistics, Mathematics, Computational Biology, or related field (or BS with equivalent experience); 6+ years of ML engineering experience with a demonstrated emphasis on production systems
* ** Production ML:
** Proven ability to deploy, maintain, and monitor ML models and pipelines at scale
* ** Python & frameworks:
** Advanced scientific Python (Num Py, Pandas,…