Senior AI Engineer
- Lead the design and implementation of enterprise-grade AI solutions aligned with business objectives and architecture standards
25 days
1,300+ Xml Jobs - November 2026 - Urgent Hiring - Page 33
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Artificial Intelligence Engineer
- Build AI prototypes and production features.
26 days
- Build agents and multi-step automations that replace manual work across finance, marketing, business development and web.
26 days
AI - Digital Engineer
- Develop and implement AI/ML, LLM, Computer Vision and predictive analytics solutions for construction projects.
26 days
Senior AI Engineer
- Design, build, and maintain autonomous AI agents that execute end-to-end business workflows in financial operations
26 days
Data Annotator | $10-hr Remote
- Review short video and audio clips, scrutinizing both visual and auditory elements for detailed annotation and assessment.
7 days
- Design, develop, deploy, and maintain AI/ML and GenAI solutions using Python for enterprise and business use cases.
26 days
AI Lead Developer, AI Products
- Design, develop, integrate and optimise scalable AI/ML solutions, including LLM-based applications, Retrieval-Augmented Generation (RAG), agentic AI and multimodal AI solutions to address Home Team use cases.
26 days
26 days
Full Time AI Trainer
- Deliver structured training programmes in Generative AI and related digital skills.
26 days
- Support in building and improving an evaluation algorithm that learns from past human decisions to assess the quality of new AI suggestions and identify when human review is required.
19 days
- Own the AI-Ready Data & Harness Engineering strategy, technical roadmap and capability architecture for Singtel SG, aligned to the AIDA 2.0 stack and Chief AIDA Officer agenda.
8 days
2026 Q4 - Artificial Intelligence Intern
- Support Automation Engineers and Managers in implementing "Lights Off" processes at Wafer Bump (WB) and Die Bond (DB) operations
26 days
Robot Learning Engineer
- Design, train, and evaluate learned policies for manipulation and whole-body control — imitation learning, reinforcement learning, and VLA-style architectures
19 days
9 days
Senior Technologist - Machine Learning
- Deep Learning Systems Architecture & Ownership : Design and own CNN, U-Net, and ViT systems for precision inspection, measurement, and defect classification. Own real-time anomaly detection from sensor and time-series product development data streams. Highest day-to-day output responsibility.
26 days
- Investigate fraud, abuse, account integrity, and platform-safety problems using data and domain knowledge.
26 days
20 days
- Educational Background & Technical Foundations Pursuing a degree in Computer Science, Data Science, Engineering, or a related field Strong fundamentals in programming (preferably Python) and SQL Basic understanding of data structures, algorithms, and software engineering principles 2. Data & AI Knowledge Familiarity with data processing concepts (ETL/ELT, data modeling, data cleaning) Exposure to machine learning fundamentals (e.g., supervised/unsupervised learning, model evaluation) Experience with common data/ML libraries (e.g., Pandas, NumPy, scikit-learn) is a plus 3. Tools & Platform Exposure Exposure to cloud platforms (e.g., AWS, Azure, or GCP) and modern data ecosystems is advantageous Familiarity with databases (SQL/NoSQL) and data warehousing concepts (e.g., Snowflake, BigQuery, Databricks) 4. Problem-Solving & Mindset Strong analytical thinking and problem-solving skills Ability to break down complex problems into structured solutions Eagerness to learn and adapt in a fast-paced, technology-driven environment 5. Communication & Collaboration Good communication skills, with the ability to explain technical concepts clearly Team player with a proactive and ownership-driven attitude Ability to work with cross-functional teams (analytics, business stakeholders)
10 days
AI Application Developer (LLM - Agentic AI)
- Lead the development and deployment of LLM-based and Agentic AI applications to address business and operational challenges.
20 days
- For large-model training and evaluation scenarios, participate in formulating and continuously iterating data quality standards, judgment rules, and acceptance criteria.
10 days
- Build and optimize cross-scenario shared Foundation Models to enable unified modeling and efficient inference.
10 days
AI Inference Acceleration Algorithm Expert
- Lead the research and development of AI training and inference acceleration algorithms for Agentic AI and Multimodal domains, specifically optimized for next-generation AI compute architectures to maximize compute efficiency and utilization.
11 days
Assistant Manager, Data - AI
- Master's or Bachelor's degree in Computer Science, Engineering, Data Science, or related discipline.
20 days
- Deep Learning Systems Architecture & Ownership : Design and own CNN, U-Net, and ViT systems for precision inspection, measurement, and defect classification. Own real-time anomaly detection from sensor and time-series product development data streams. Highest day-to-day output responsibility.
27 days
- Proactively assist in the management of Financial Crime and / or Third-Party Risk Management client and business development projects, while reporting to supervisors
16 days
AI Researcher (2 Yr Contract)
- Work with structured datasets to identify patterns, trends, and statistically significant findings that inform research questions and business decisions.
27 days
- Design, build, and deploy LLM-powered features and applications using Python.
20 days
- Build agents and multi-step automations that replace manual work across finance, marketing, business development and web.
27 days
- Educational Background & Technical Foundations Pursuing a degree in Computer Science, Data Science, Engineering, or a related field Strong fundamentals in programming (preferably Python) and SQL Basic understanding of data structures, algorithms, and software engineering principles 2. Data & AI Knowledge Familiarity with data processing concepts (ETL/ELT, data modeling, data cleaning) Exposure to machine learning fundamentals (e.g., supervised/unsupervised learning, model evaluation) Experience with common data/ML libraries (e.g., Pandas, NumPy, scikit-learn) is a plus 3. Tools & Platform Exposure Exposure to cloud platforms (e.g., AWS, Azure, or GCP) and modern data ecosystems is advantageous Familiarity with databases (SQL/NoSQL) and data warehousing concepts (e.g., Snowflake, BigQuery, Databricks) 4. Problem-Solving & Mindset Strong analytical thinking and problem-solving skills Ability to break down complex problems into structured solutions Eagerness to learn and adapt in a fast-paced, technology-driven environment 5. Communication & Collaboration Good communication skills, with the ability to explain technical concepts clearly Team player with a proactive and ownership-driven attitude Ability to work with cross-functional teams (analytics, business stakeholders)
11 days