Informatica Senior Machine Learning Engineer 

Singapore, Singapore 

10279253

Responsibilities:

• Drive design for AI and ML related model pipelines, and services.
• Collaborate with cross-functional teams, including stakeholders, to identify opportunities for developing end-to-end AI architectures for diverse industry scenarios.
• Passion for applying state-of-the art AI algorithms to real-world problems.
• Stay up to date with the latest developments in AI and related fields, evaluate new developments and technologies for potential integration into existing and future architecture.
• Provide solutions that foster ML Engineer developer productivity.
• Lead the development and deployment of machine learning models, deep learning algorithms, and other AI/ML techniques. Ensure best practices for model training, testing, and validation are followed.

Requirements:

• Understand and hands-on experience developing ML models ranging from regression to deep neural networks including LLMs.
• Experience building and scaling platform-centric infrastructure is desired.
• Experience working with ML Ops pipelines
• Familiarity with modern techniques for Language Understanding, and other Machine Learning and AI technologies
• Work well with local and global team of engineers, researchers, and product managers.
• Master's degree in computer science, Electrical Engineering or related fields with focus on AI and machine learning.
• 3-7 years of industry and research experience in Artificial Intelligence and Machine Learning
• Experience with AWS, Google or Azure is Required
• Experience and understanding of modern ML pipelines using Kubeflow, KServe, Hugging Face, and similar toolkits.
• BA/BS or equivalent educational background, we will consider an equivalent combination of relevant education and experience
• Minimum 2+ years of relevant professional experience

• Comprehensive health, vision, and wellness benefits (Paid parental leave, adoption benefits, life insurance, disability insurance and 401k plan or international pension/retirement plans
• Flexible time-off policy and hybrid working practices
• Tuition reimbursement program to support your and personal growth
• Equity opportunities and an employee stock purchase program (ESPP)
• Comprehensive Mental Health and Employee Assistance Program (EAP) benefit