THE ROLE:
As a Senior Full-stack Machine Learning Developer (Health Care practice), you will have the opportunity to work with leading institutions in the healthcare and life sciences sectors, deploying cutting-edge, end-to-end ML & AI solutions. You will tackle complex challenges in medical diagnostics, drug discovery, clinical decision support, and patient outcome modeling, leveraging AI to drive meaningful impact in healthcare delivery, precision medicine, and operational efficiency.
THE PERSON:
We are highly selective about who we bring on board and appreciate your attention to the following:
- Submitting a tailored CV
- Completing a 60-second video interview explaining what sets you apart
- Participating in a technical assessment
- (Optional) Sharing a GitHub project you are particularly proud of
At a high level, the ideal candidate possesses the following qualifications:
- 7+ years of experience in a consulting or BigTech environment, deploying ML, Deep Learning, NLP, Classification, Regression, and Generative AI use cases across the healthcare spectrum.
- Full-stack expertise in Python, Java, JavaScript, or Julia for ML model development, with backend infrastructure experience in data staging, transformation, and deployment across AWS, Azure, and Snowflake.
- Extensive experience working with large-scale healthcare datasets, including EHRs, medical imaging, genomics, real-world evidence (RWE), and other clinical data.
- Strong AI & ML domain expertise in healthcare applications, such as predictive diagnostics, clinical decision support, patient outcome modeling, drug discovery, and medical imaging analysis.
KEY RESPONSIBILITIES:
- Develop and deploy ML, Deep Learning, NLP, Classification, Regression, and Generative AI solutions for healthcare applications, including predictive diagnostics, clinical decision support, patient outcome modeling, drug discovery, and medical imaging analysis.
- Build and maintain full-stack AI/ML applications, leveraging Python, Java, JavaScript, or Julia, with backend infrastructure expertise in data staging, transformation, and deployment across AWS, Azure, and Snowflake.
- Work with large-scale healthcare datasets, including EHRs, medical imaging, genomics, and real-world evidence (RWE), ensuring high-quality data processing and model training.
- Lead and contribute to the full AI/ML development lifecycle, including supervised, semi-supervised, unsupervised, and reinforcement learning use cases.
- Optimize and deploy deep learning models, particularly transformers, using frameworks like PyTorch and TensorFlow.
- Architect and manage scalable backend infrastructure, ensuring robust data pipelines and cloud/on-premises enterprise architecture.
- Communicate technical insights effectively in a client-facing role, requiring native English or C2 proficiency and strong presentation skills, including experience engaging with senior management.
- Thrive in fast-paced, evolving environments, managing tight deadlines and ambiguous requirements.
- Periodic travel may be necessary.
PREFFERED EXPERIENCE:
- Experience in Computer Vision, particularly in medical imaging and radiology AI.
- Expertise in training and fine-tuning large language models, including distillation and supervised fine-tuning techniques.
- Proficiency in federated learning and privacy-preserving ML, with a focus on healthcare data security and decentralized learning.
- Hands-on experience in robotics or machine vision for medical AI applications.
ACADEMIC CREDENTIALS:
Love what we do but not finding a position that connects with you? Drop us an email with a CV and a few words about yourself. If we like what we see, we will get in touch. hi@serious.co
