Artificial Intelligence Engineer

Our client is building the next generation of cancer surveillance technology to help detect risk earlier, personalize screening strategies, and improve outcomes for cancer survivors. Their platform combines advanced machine learning, clinical data, and longitudinal patient insights to create intelligent systems that support clinicians and patients throughout the cancer journey. They are looking for an exceptional AI Engineer to design, build, and deploy the machine learning systems powering our cancer surveillance platform. This is an early-stage opportunity to have significant impact on our technical foundation, working closely with our AI leadership, clinical experts, and product team. The Role As an AI Engineer, you will build the machine learning infrastructure and models that transform complex biomedical data into actionable clinical insights. You will take research concepts from prototype through production, developing AI systems that support cancer biomarker detection, risk prediction, longitudinal monitoring, and personalized screening strategies. You will report to the Head of AI and collaborate closely with clinicians, data scientists, product leaders, and software engineers. This is an in-person role based in our Boston office, with the opportunity to shape both our technology and engineering culture from the ground up. What You’ll Do Design, develop, train, evaluate, and deploy machine learning models for: Longitudinal patient monitoring Personalized screening and survivorship recommendations Translate research models into reliable, production-ready systems Develop and optimize deep learning architectures, including foundation models and multimodal learning approaches Build scalable machine learning pipelines covering: Performance monitoring Develop cloud-based ML infrastructure using platforms such as AWS or GCP Leverage GPU/accelerated computing environments for large-scale model development Implement strong engineering practices including: Version control Testing

CI/CD

Biomedical Data & Clinical AI Partner with clinical and data teams to curate, validate, and manage complex datasets from sources including: Genomics Medical imaging Electronic health records (EHR) Other multimodal healthcare data sources Build evaluation frameworks to ensure model performance, reliability, and clinical relevance Collaborate with clinicians and scientific stakeholders to align AI capabilities with real-world healthcare workflows Bridge cutting-edge AI research with practical clinical applications Support development and refinement of AI systems as the platform evolves Contribute to technical strategy and architecture decisions as an early engineering team member What You Bring Required Qualifications MS or PhD in Computer Science, Machine Learning, Computational Biology, Bioinformatics, or a related quantitative field 3+ years of hands-on experience building and deploying machine learning models in production environments Strong programming skills in Python Experience with modern machine learning frameworks such as: PyTorch TensorFlow JAX Experience building ML pipelines and deploying models in cloud environments (AWS, GCP, or similar) Experience with containerized development environments (Docker) Strong software engineering fundamentals: Git/version control Testing Ability to communicate complex technical concepts clearly with both technical and non-technical stakeholders Preferred Qualifications Experience working with healthcare or biomedical datasets, including: Genomics Pathology Imaging EHR data Experience developing AI systems in healthcare, biotech, or life sciences environments Publications, research contributions, or open-source work in: Machine learning Computational biology Experience working in an early-stage startup environment Entrepreneurial mindset with a willingness to take ownership and solve ambiguous problems #J-18808-Ljbffr TAPPS