Machine Learning (ML) Engineer II
Skills
Computer ScienceArtificial IntelligenceCustomer RequirementsData ScienceMachine LearningNatural Language ProcessingPattern Recognition
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Leverage proprietary technology stack to build custom machine learning models
- Design, implement, and document new ML/NLP modeling techniques
- Develop back-end software to support AI solution development
- Build internal frameworks, libraries, and infrastructure to improve ML and NLP capabilities for rapid prototyping and new product delivery
- Review and improve code of other engineers to enhance ML quality and security
- Develop custom models and AI/NLP solutions to address business needs
- Lead experiment and evaluation design
- Collaborate with Product to define and implement features
- Partner with application engineering to build high quality production software
- Contribute to establishing standards in applied ML/AI
- Create educational content for AI literacy and guide appropriate AI usage across the company
- Act as an AI expert advisor within Parexel
Nice to have
- Flexible attitude
- Enthusiastic
- Detail-oriented
Day to day
- Work within our AI Labs’ department to build and deploy AI-driven solutions to improve workflows common across Parexel and the life sciences industry
- Develop production ready AI-based solutions for key impact areas in Parexel’s business by writing, testing, and releasing code and internal libraries
- Collaborate with application engineering, product, and business stakeholders to develop ML solutions from research to POC to production
- Leverage proprietary technology stack to build custom ML models and design new ML/NLP modeling techniques and strategies
- Build internal frameworks, libraries, and infrastructure for rapid prototyping and new product delivery