Senior/Staff Machine Learning Engineer – Model Dev

Job not on LinkedIn

🕒 September 18

🇺🇸 United States – Remote

💵 $180k - $240k / year

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 0%

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Artera.net

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2002

💼 Consulting

📦 Logistics

📣 Marketing

Consulting • Logistics • Marketing

Artera. net is a leader in providing B2A (Business to Agency) solutions, specializing in premium hosting and cloud services tailored for agencies and their digital needs. The company offers a comprehensive array of services including hosting, cloud server, and cloud enterprise solutions. Artera. net emphasizes innovation, reliability, and security, boasting high-quality infrastructure with proprietary data centers in Switzerland, robust anti-DDoS protection, and compliance with privacy regulations including GDPR. Their offerings include pro-active 24/7 support with direct communication with system experts, ensuring high levels of customer satisfaction with a renewal rate of 93%. Artera. net also promotes environmental sustainability by powering its data centers with renewable energy. With a partnership program for web companies, software houses, and freelancers, Artera. net aims to build long-term, trust-based relationships while offering customized and flexible technology solutions that cater specifically to the needs of each project.

📋 Description

• Lead the technical effort and define the strategic vision for patient-facing products with product, biostatistics, clinical development, and regulatory/quality teams • Design and build AI-based biomarkers using whole-slide images, clinical variables, and molecular data to predict patient outcomes, treatment benefit, and molecular traits • Advance self-supervised foundation models and downstream architectures, including multiple-instance learning, time-to-event/hazard models, segmentation, and classification • Own score reproducibility across scanners, institutions, staining protocols, and patient populations • Develop and integrate mechanistic interpretability methods to explain model decisions and improve models • Architect tools and processes for the end-to-end model development lifecycle from prototyping through production deployment and monitoring • Author and defend regulatory and quality documentation and represent AI in design and development reviews • Plan and manage multi-quarter delivery milestones, dependencies, risks, submission dates, and launch dates • Publish in peer-reviewed journals and present at clinical and ML venues; support external collaborations • Mentor and coach machine-learning scientists and engineers and raise standards for scientific rigor, code quality, and written communication

🎯 Requirements

• 5+ years of industry experience building deep learning systems in PyTorch (or TensorFlow) • 2+ years of experience as a technical lead, launching and monitoring machine-learning products in production environments • Demonstrated depth in oncology and biomarker development, including familiarity with cancer biology and treatment pathways, clinical endpoints, risk stratification, and clinically actionable biomarkers • Demonstrated project management ability, including scoping, sequencing, and managing dependencies and risk across multiple teams on dated deliverables • Proven ability to communicate complex ML concepts effectively to cross-functional, non-ML collaborators • Experience mentoring or managing ML scientists and engineers • Experience building ML on complex clinical data, including medical imaging, multi-omics, or longitudinal patient records, weakly supervised learning, and variation across sites, devices, and protocols • Experience developing ML in a regulated environment, such as FDA 510(k)/De Novo, CE/UKCA, SaMD, design controls, or CLIA/LDT validation • Experience with self-supervised representation learning and adapting medical foundation models to downstream clinical tasks • Experience with randomized controlled trial data and multi-institutional clinical cohorts • Peer-reviewed publications and conference presentations, with external academic or industry collaborations • Experience with cloud-scale training and workflow orchestration, experiment tracking, and reproducible ML pipelines

🏖️ Benefits

• Equity • 401k matching • Unlimited paid time off (PTO)