Machine Learning Bioinformatics Engineer

Company Description

At Copoly.ai, we are a dynamic biotech and AI company driving innovation by working on our own proprietary products and developing specialized solutions for our clients. We are transforming the future of early cancer detection through AI-powered diagnostic solutions. Our flagship product, OncoSage, leverages RNA sequencing and proprietary machine learning algorithms to deliver accurate, blood-based cancer detection. We are committed to advancing the field of oncology through cutting-edge technology, improving patient outcomes, and detecting cancer at its earliest stages. Join us in our mission to make revolutionary strides in healthcare technology.

Overview

We are seeking a talented and passionate Machine Learning Engineer to develop and deploy cutting-edge machine learning solutions that leverage complex biological and clinical data. In this role, you will have the unique opportunity to analyze and model large, multimodal clinicogenomic datasets that integrate genomic, transcriptomic, clinical, and real-world patient data at scale. By applying advanced machine learning approaches to these datasets, you will help uncover novel biomarkers, stratify patient populations, and generate actionable discoveries that inform drug development and precision medicine.

Responsibilities

* Develop and deploy maintainable, scalable, and reliable machine learning models while applying principles of modular design and testing.

* Handle and process large-scale cancer genomic and transcriptomic datasets, converting RNA and DNA data into high-quality deliverables for clinicogenomic correlations.

* Scale model training by utilizing frameworks like PyTorch Lightning and Hugging Face Transformers.

* Build and deploy scalable ML solutions in cloud environments (AWS/GCP), emphasizing reproducibility.

* Collaborate closely with ML and translational research scientists to generate novel insights on disease biology, treatment resistance, and therapeutic targets.

* Provide design guidance and technical leadership for components of large-scale machine learning projects.

Qualifications & Requirements

* Education & Experience: PhD with 0–2 years of relevant experience, MS with 3–5 years of relevant experience, or BS with 4–7 years of relevant experience.

* Programming Skills: Strong proficiency in Python with extensive experience using ML and data libraries, including NumPy, pandas, and PyTorch.

* Machine Learning Expertise: Excellent knowledge of modern ML methods, training strategies, model validation, performance visualization, and experimental design.

* Bioinformatics & Domain Knowledge: Proficient knowledge of bioinformatic processing pipelines for genomic and transcriptomic variables, alongside a strong understanding of computational oncology and clinicogenomics datasets.

* Soft Skills: Strong technical writing and communication skills.

Benefits:

* Dental care

* Extended health care

* Paid time off

* RRSP match

* Vision care

* Work from home

Application questions:

* Which coding language did you use most recently and most frequently?

* Do you know how to implement survival models? Provide examples.

* Have you worked with clinicogenomics data? Provide examples.

Work Location: Remote