Join the Platform Architecture Group, collaborate with Staff Engineers and architects and provide high-level end-to-end solution design for the company’s mission critical initiatives.
Design ML Architecture across multiple ML and Data Teams in order to build robust, scalable and production-ready solutions that enhance the speed and quality of life-saving research.
Write, review and approve ML and Data technical documentation to ensure quality and accuracy of performance and results.
Contribute to the ML and Data roadmap by ensuring project proposals are both highly impactful and technically feasible.
Continuously improve our workflows by keeping up to date with the latest optimizations in libraries such as PyTorch, and expand our usage of modern tools such as DVC.
Own ML solutions and long-term technical investments that will drive innovation at BenchSci.
Lead technical design discussions, apply best practices, diagnose problems, and lead the resolution while fostering an inclusive environment. Participate and contribute to Agile grooming, planning, and estimation.
Promote the definition of coding guidelines and raise the bar for code quality using tools such as SonarCloud.
Provide guidance to senior engineers and help to foster a culture of continuous growth.
Work cross-functionally with different stakeholders including BenchSci’s R&D scientists to learn, model, and capture the nuances of biology.
Requirements & Skills:
At least 8 years of professional experience applying ML techniques to solve business problems, with at least 2 years at a Staff Engineer level.
Strong experience with NLP and LLMs. Strong experience with Python and programming fundamentals.
Extensive experience with PyTorch.
Track record of successfully delivering robust, scalable, and production-ready ML models.
Experience with the full ML development lifecycle from architecture and technical design, through data collection and preparation, model selection, training and evaluation, to deployment and maintenance.
Experience with data manipulation and processing, such as SQL or pandas.
Experience with Cloud solutions and Cloud architecture, in particular with MLOps, DataOps, and data warehouses.
Experience leading technical design discussions, writing and reviewing technical design documents, and providing technical guidance and directions.
Ability to reason about trade-offs and make technical decisions under a certain level of uncertainty.
Strong cross-team communication and collaboration skills. A growth mindset and a constant desire to learn.
