If you have a Candidate Login already, but have forgotten your password please use the steps to reset your password. If you have forgotten your email login, please contact servicedesk@welocalize.com subject Workday Candidate Login
When creating your Workday account and entering personal information like name, address, please do not use ALL CAPS.
Thank you!
NOTICE: For Privacy Policy please review here
Job Responsibilities:
MAIN TASKS & RESPONSIBILITIES
The following is a non-exhaustive list of responsibilities and areas of ownership of an AI/ML Engineer
- Design and develop machine learning models and algorithms for various aspects of the localization and business workflow processes, including machine translation, LLM finetuning, and quality assurance
- Take ownership of key projects from definition to deployment, ensuring that they meet technical requirements and maintain momentum and direction until delivery
- Evaluate and select appropriate machine-learning techniques and algorithms to solve specific problems
- Implement and optimize machine learning models and technologies using Python, TensorFlow, and other relevant tools and frameworks
- Perform statistical analysis and fine-tuning using test results
- Deploy machine learning models and algorithms using appropriate techniques and technologies, such as containerization using Docker and deployment to cloud infrastructure
- Use AWS technologies (including but not limited to Sagemaker, EC2, S3) to deploy and monitor production environments
- Keep abreast of developments in the field, with a dedication to learning in the role
- Document diligently and communicate thoughtfully about ML experimentation, design, and deployment
- Project scope: Define and design solutions to machine learning problems. Integration with larger systems done with the guidance of more senior engineers.
Success Indicators for a Machine Learning Engineer
- Effective Model Development: Success is evident when the models developed are accurate, efficient, and align with project requirements.
- Positive Team Collaboration: Demonstrated ability to collaborate effectively with various teams and stakeholders, contributing positively to project outcomes.
- Continuous Learning and Improvement: A commitment to continuous learning and applying new techniques to improve existing models and processes.
- Clear Communication: Ability to articulate findings, challenges, and insights to a range of stakeholders, ensuring understanding and appropriate action.
- Ethical and Responsible AI Development: Adherence to ethical AI practices, ensuring models are fair, unbiased, and responsible.
REQUIREMENTS
Education
- BSc in Computer Science, Mathematics or similar field; Master’s degree is a