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 EMEA Jobs, please review the Privacy Policy here
Job Responsibilities:
The Senior AI/ML Platform Engineer is responsible for leading the design, implementation, and optimization of scalable machine learning infrastructure. This role ensures that AI/ML models are efficiently deployed, managed, and monitored in production environments while providing mentorship and technical leadership to junior engineers.
Key Responsibilities
- Architectural Leadership: Lead the design and development of scalable, secure, and efficient AI/ML platform architecture, ensuring robust and reliable infrastructure.
- Automation & Deployment: Develop and implement advanced automation pipelines for model deployment, monitoring, and rollback, enhancing operational efficiency.
- Cross-Functional Collaboration: Collaborate with cross-functional teams, including data scientists and product managers, to define platform requirements and support seamless model integration.
- Performance Optimization: Drive performance tuning, load balancing, and cost optimization strategies to ensure the platform's efficiency and scalability.
- Mentorship & Leadership: Mentor junior platform engineers, providing technical guidance and fostering a culture of best practices and continuous learning.
- Incident Management: Conduct post-mortems and root cause analysis for system failures and performance issues, implementing corrective actions to prevent recurrence.
Education:
- Educational Background: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
Experience:
- 5+ years of experience in AI/ML platform or infrastructure engineering, with a proven track record in leading and executing complex projects.
Technical Expertise:
- Expertise in cloud-based solutions (e.g., AWS, GCP, Azure), distributed systems, and microservices architecture.
- Proficiency in Terraform, Docker, and advanced automation tools.
- Proficiency in python and node.js.
- Strong understanding of machine learning frameworks (e.g., TensorFlow, PyTorch) and MLOps practices.
Problem-Solving Skills: Excellent problem-solving skills with a proactive approach to identifying and addressing technical challenges.
Leadership Skills: Strong leadership and mentoring skills, with the ability to guide and inspire engineering teams.
Communication Skills: Excellent communication skills, with the ability to articulate technical concepts to both technical and non-technical stakeholders.
Additional Job Details:
Read Full Description