Machine Learning Engineer (Remote)

Machine Learning Engineer (Remote)ClinicalSouth San Francisco, California, USAdded - 30/04/2026Our client is a leader in healthcare innovation, seamlessly integrating pharmaceutical development, diagnostic solutions, and advanced technology and data capabilities.Title: Machine Learning Engineer (Contract)Pay rate: $55-73/hr+ (Depends on experience)Location: Remote in the US or Canada, or onsite in SSF. Must be available during PST hours.Duration: Through Dec. 2026 (Likely to get extended)Overview:Seeking a Machine Learning Bioinformatics Engineer to develop and deploy advanced ML solutions supporting pharmaceutical R&D. This role focuses on analyzing large-scale, multimodal clinicogenomic datasets (genomic, transcriptomic, clinical, and real-world data) to drive insights into disease biology, patient stratification, and treatment response. Ideal candidates are strong in both machine learning and bioinformatics, with a passion for translating complex data into impactful discoveries.Key Responsibilities:Build and deploy scalable, production-ready machine learning modelsProcess and analyze genomic and transcriptomic data using bioinformatics pipelinesPrepare high-quality, normalized biological datasets for downstream analysisTrain large-scale models using frameworks like PyTorch Lightning and Hugging FaceDevelop cloud-based ML solutions (AWS/GCP) with a focus on scalability and reproducibilityCollaborate with cross-functional teams to uncover biomarkers and therapeutic targetsProvide technical input and guidance on ML system design and implementationQualifications:PhD with 0-2 years of relevant work experience, or MS with 3-5 years of relevant work experience, or BS with 4-7 years of relevant work experience.Proficient programming skills: Strong Python programming skills with extensive experience in ML and data libraries (e.g., NumPy, pandas, PyTorch).Deep ML expertise: Excellent knowledge of modern machine learning methods and development best practices, including training strategies, model validation, performance visualization, and experimental design.Deep bioinformatic expertise: Proficient knowledge of bioinformatic processing pipelines for genomic and transcriptomic variables.Strong knowledge of computational oncology, cancer genomics and analysis of clinicogenomics datasets.Must be authorized to work in the United StatesINDBH#LI-MG1We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law.