Building scalable machine learning pipelines, including efficient parallelization and use of GPUs; Designing and coding data processing pipelines, ownership of company-wide data platform; Working closely with Platform Development and Biology teams to automate a tight design-build-test cycle for ML generated small molecules; Working in a collaborative CI/CD software development environment, including use of git, participating in code reviews, and independent development of robust code; Working within an entrepreneurial, collaborative, and interdisciplinary team to actively contribute to creating, shaping, and executing the vision of the company
Requirements:
Undergraduate or Master's degree in bioinformatics, computer science, mathematics, physics or related field and 4+ years of experience is required; Experience with MLOps practices and tools including version control, automated testing, and CI/CD; Proficient in Python and experience in using deep learning libraries (i.e. PyTorch); Experience with cloud computing (i.e. AWS), database scale-out (e.g. distributed postgresql), and data pipelining tools (i.e. Nextflow, Airflow); Experience with Slurm or other on-site HPC cluster solutions
Text:
(Senior) Machine Learning Engineer Building scalable machine learning pipelines, including efficient parallelization and use of GPUs; Designing and coding data processing pipelines, ownership of company-wide data platform; Working closely with Platform Development and Biology teams to automate a tight design-build-test cycle for ML generated small molecules; Working in a collaborative CI/CD software development environment, including use of git, participating in code reviews, and independent development of robust code; Working within an entrepreneurial, collaborative, and interdisciplinary team to actively contribute to creating, shaping, and executing the vision of the company Undergraduate or Master's degree in bioinformatics, computer science, mathematics, physics or related field and 4+ years of experience is required; Experience with MLOps practices and tools including version control, automated testing, and CI/CD; Proficient in Python and experience in using deep learning libraries (i.e. PyTorch); Experience with cloud computing (i.e. AWS), database scale-out (e.g. distributed postgresql), and data pipelining tools (i.e. Nextflow, Airflow); Experience with Slurm or other on-site HPC cluster solutions
Please click here, if the job didn't load correctly.
Please wait. You are being redirected to the job in 3 seconds.
