remoteonsite
Architect - Machine Learning - Quantiphi
ML Engineer
Lead end‑to‑end ML solutions in healthcare, designing scalable architectures on AWS, building data pipelines, and driving model deployment and monitoring. Requires deep expertise in Python, deep learning frameworks, and cloud‑native ML services.
About the role
Key Responsibilities
- Design and architect robust, scalable machine learning pipelines for healthcare applications on AWS.
- Lead end‑to‑end model development, from data ingestion and feature engineering to training, validation, and deployment.
- Collaborate with data scientists, data engineers, and product teams to translate business requirements into technical solutions.
- Implement model monitoring, governance, and continuous improvement processes to ensure high quality and compliance.
- Mentor junior team members and promote best practices in ML engineering and cloud architecture.
Requirements
- 8+ years of experience in machine learning engineering and architecture.
- Proficiency in Python, deep learning frameworks (TensorFlow, PyTorch), and data engineering tools.
- Hands‑on experience with AWS services such as SageMaker, Lambda, S3, and Glue.
- Strong understanding of healthcare data standards and regulatory compliance.
- Excellent communication skills and ability to work cross‑functionally in a fast‑paced environment.
Skills
machine learningpythonawsdeep learning