- Bachelor’s degree in Engineering, Computer Science, Information Systems, or a related technical discipline
- Experience supporting manufacturing or quality systems in regulated environments (pharmaceutical, biotech, or life sciences)
- Experience with Line Clearance processes and Machine Learning applications
- Strong troubleshooting, analytical, and problem-solving skills
- Ability to work effectively in an on-site, cross-functional environment
- Strong written and verbal communication skills
- Experience supporting production-grade AWS-based machine learning platforms, including:
- AWS SageMaker Pipelines for ML workflow orchestration
- Model versioning and governance using Amazon SageMaker Model Registry or equivalent tools
- Deployment and operation of ML solutions across multi-account AWS environments (development, validation, and production)
- Understanding of MLOps best practices, including model lifecycle management, CI/CD for ML, monitoring, and controlled promotion across environments
- Familiarity with AWS Well-Architected Framework principles, particularly security, reliability, and operational excellence, as applied to ML platforms
Preferred Qualifications
- Experience working in GMP-regulated manufacturing environments
- Exposure to system validation, change control, and regulated documentation practices
- Experience supporting cloud-based data or analytics platforms in life sciences
- Knowledge of pharmaceutical manufacturing workflows and quality systems
- Prior experience supporting Amgen systems or similar enterprise manufacturing environments
Disclaimer on the Use of AI in our Recruitment Process
To ensure our hiring process is fair, ethical, and transparent, ATS incorporates the use of AI technologies to enhance the recruitment process. We utilize Microsoft CoPilot to assist with the development and posting of job descriptions and assist with recruitment administrative tasks. The software uses pre‑defined, rule‑based filters which operate on fixed criteria and do not perform autonomous evaluation or generate independent recommendations. Microsoft Team Transcript is used to capture and document candidate interviews. Prior to the start of any interview, you will be asked if you consent to the use of transcript. The decision is yours and it will be honored by ATS.
The use of AI within our recruitment process is governed by the following core principles:
- Human Oversight and Accountability – AI is used solely to augment, not replace human judgment. All decisions regarding CV/resume screening, who to interview, and who to hire are made by ATS hiring managers and recruitment teams.
- Transparency and Data Protection – ATS will inform candidates when AI is being used to transcribe an interview to ensure our notes are complete and accurate. Candidates may choose whether or not to allow the use of transcript. All applicant data, including AI-generated interview notes, is treated as a confidential recruitment record and managed in accordance with applicable data protection laws.
- Fairness and Equality – ATS is committed to ensuring the use of AI is vetted and assessed to ensure it is not creating or perpetuating bias or discrimination.
