We're looking for a talented Senior Machine Learning Engineer with a strong technical background in computer science and database management to lead the design and development of machine learning platforms and infrastructure. You will collaborate with cross-functional teams, act as a technical lead, and mentor others while supporting the advancement of innovative medical technologies.

🎯 Responsibilities

1. Act as the central technical liaison between project stakeholders and the Data Science team, owning the integration and deployment of algorithms and machine learning models into production workflows
2. Design, build, and scale cloud-native and hybrid data and machine learning (MLOps) platforms tailored for Data Science teams
3. Plan, architect, and develop long-term enterprise tooling and infrastructure to accelerate and streamline ML model research, training, and evaluation
4. Take responsibility for end-to-end software and data architecture within Data Science initiatives, driving the specification, implementation, and testing of complex technical assignments
5. Serve as a technical lead and subject matter expert; gather requirements, continuously improve the ML platform, and mentor peers to foster a culture of engineering excellence

🛠️ Requirements

1. Degree in Computer Science, Software Engineering, or a related technical field
2. Extensive professional experience in software engineering with Python, including strong knowledge of application architecture and design patterns
3. Strict adherence to coding best practices (e.g., TDD, ATDD), rigorous testing strategies, and effective version control
4. Deep understanding of full ML workflows and hands-on experience provisioning the necessary infrastructure
5. Significant experience with various storage technologies (Relational Databases, NoSQL, Object Storage) and understanding of their trade-offs
6. Solid knowledge and hands-on experience with High-Performance Computing (HPC) and AWS-based data engineering and analytics solutions
7. Expertise in the Python data ecosystem (NumPy, Pandas, Scikit-learn), proficiency in Linux environments, and hands-on experience with modern data integration, ETL, and MLOps tools

➕ Nice to have

1. Domain knowledge or strong interest in life sciences, especially Sequencing, PCR, Bioinformatics, or digital healthcare
2. Experience building, deploying, or working with Large Language Models (LLMs) and agentic systems
3. Official Cloud certifications (e.g., AWS Certified Solutions Architect – Professional)
4. Proven experience working in large, globally distributed, or international enterprise environments