Machine Learning Scientist, Multimodal AI

🕒 July 30

🇺🇸 United States – Remote

💵 $124.8k - $171.6k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 18%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Natera

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2004

🏥 Healthcare

🧬 Biotechnology

⚕️ Healthcare Insurance

Healthcare • Biotechnology • Healthcare Insurance

Natera is a global leader in cell-free DNA testing technology, specializing in non-invasive genetic testing and diagnostics. The company's innovative solutions focus on areas such as prenatal screening, cancer detection, and organ transplant monitoring. By using advanced bioinformatics and DNA analysis, Natera provides healthcare professionals and patients with critical information to make more informed medical decisions.

📋 Description

• Design, implement, and evaluate deep learning models across biomedical data modalities, including histopathology imaging, genomic sequencing, transcriptomics, and cfDNA features • Develop multimodal AI architectures integrating H&E whole-slide imaging with molecular and clinical data • Build scalable, production-quality machine learning workflows and pipelines using AWS cloud infrastructure • Apply CNNs, vision transformers, sequence transformers, representation learning, and foundation model fine-tuning • Collaborate with technical and clinical teams to translate machine learning prototypes into validated tools • Analyze model outputs to generate reproducible biological and clinical insights • Document pipelines thoroughly and communicate data-driven findings to cross-functional stakeholders

🎯 Requirements

• PhD in Computer Science, Computational Biology, Biomedical Engineering, Bioinformatics, Statistics, or a related quantitative discipline with a focus on machine learning or AI • Core experience developing machine learning models for biomedical applications, specifically in medical imaging, computational pathology, genomics, transcriptomics, multi-omics, or molecular diagnostics • Hands-on expertise with PyTorch and strong production-level programming skills in Python • Practical application of deep learning architectures such as CNNs, transformers, attention mechanisms, and representation learning • Experience managing datasets and training workflows within distributed or cloud computing environments (AWS) • Proven ability to take ownership of research projects and translate prototypes into robust, deployment-ready workflows • Experience adapting pre-trained foundation models for downstream biomedical applications • Preferred: experience integrating imaging, molecular, and clinical data within unified multimodal machine learning frameworks • Preferred: technical familiarity with DNA sequencing, RNA sequencing, methylation, and ctDNA assays • Preferred: hands-on experience with digital pathology software and whole-slide imaging analysis • Preferred: exposure to survival modeling, longitudinal prediction, or time-to-event modeling • Preferred: experience applying self-supervised learning, weakly supervised learning, or multiple instance learning (MIL) to clinical data • Preferred: domain knowledge in oncology, biomarker discovery, or clinical precision medicine • Preferred: track record of peer-reviewed publications in machine learning or computational biology conferences and journals

🏖️ Benefits

• Comprehensive medical, dental, vision, life and disability plans for eligible employees and their dependents • Free testing for employees and their immediate families • Fertility care benefits • Pregnancy and baby bonding leave • 401k benefits • Commuter benefits • Employee referral program