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# (Remote) Senior AI & Machine Learning Engineer

- **Company:** Glints LLC
- **Location:** Singapore, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Artificial Intelligence, Computer Vision, Software Quality, Learning Management Systems, Information Engineering, Graph Database, Python (Programming Language), Machine Learning, Natural Language Processing, Performance Tuning, Recommender Systems, Tensorflow, Speech Recognition, Feature Engineering, Data Ingestion, Pytorch, LangChain, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Model Validation, Llamaindex, Agentic-AI, Knowledge Engineering, AI Platforms, Information Technology, HuggingFace, CrewAI, AutoGen, Machine Learning Operations
- **Published:** October 16, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/ps087ybykk

## About the Role

* 5+ years of hands-on experience in AI/ML engineering, ML systems, or data engineering, with proven experience deploying AI/ML products to production.
 * Strong proficiency in Python, with experience in PyTorch, TensorFlow, and Hugging Face.
 * Practical experience with LLM/SLM fine-tuning, RAG, prompt engineering, and model evaluation.
 * Hands-on experience with Agentic AI frameworks such as LangGraph, LangChain, LlamaIndex, AutoGen, or CrewAI., * Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, or a related field.
 * 5+ years of hands-on experience in AI/ML systems or data engineering, with a proven track record of bringing AI/ML products into production.
 * Strong proficiency in Python and experience with ML frameworks such as PyTorch, TensorFlow, and Hugging Face.
 * Proven experience fine-tuning and evaluating LLMs/SLMs using domain-specific data, including RAG, prompt engineering, and model benchmarking.
 * Strong experience with Agentic AI frameworks and patterns, including multi-agent orchestration, tool use, planning, and expert routing.
 * Hands-on experience with knowledge graphs and graph databases, including ontology modelling and schema design.
 * Experience with multimodal AI, particularly speech processing (ASR, prosody) and/or computer vision (OCR, handwriting recognition, diagram understanding), is highly desirable.
 * Demonstrated ability to mentor engineers and lead technical initiatives from concept to delivery.
 * Strong problem-solving, communication, and cross-functional collaboration skills.
 * Genuine interest in education and applying AI to improve learning outcomes.

## Description

Our client is looking for a Senior AI & Machine Learning Engineer to lead the design, architecture, and deployment of intelligent systems that power personalised learning experiences at scale.

 * You will drive AI/ML innovation across LLMs, Agentic AI, NLP, recommendation systems, and adaptive learning algorithms. Working closely with product, engineering, and business stakeholders, you will shape technical direction, build reliable production-grade AI solutions, and mentor junior engineers.
 * This role is ideal for an experienced AI/ML engineer who enjoys solving complex technical challenges and applying advanced AI technologies to real-world educational applications., 1. AI/ML Development & Deployment
 * Lead the design, development, and deployment of scalable, production-ready AI/ML systems.
 * Build end-to-end ML pipelines covering data ingestion, feature engineering, model training, evaluation, deployment, and monitoring (MLOps).
 * Monitor and optimise deployed models for performance, reliability, and scalability.

 2. AI Research & Application
 * Research and experiment with LLMs, Agentic AI, NLP, recommendation systems, and adaptive learning algorithms.
 * Develop and optimise LLM/SLM applications, including fine-tuning, RAG pipelines, and intelligent AI agents.
 * Evaluate emerging AI technologies, tools, and frameworks to enhance platform capabilities.

 3. Knowledge Engineering
 * Design and implement knowledge graphs, graph databases, and domain-specific knowledge structures to support intelligent learning systems.

 4. Collaboration & Technical Leadership
 * Collaborate with product, engineering, and business teams to translate user needs into measurable AI solutions.
 * Mentor junior AI/ML engineers and establish best practices for code quality, testing, reproducibility, and responsible AI.

 5. Technical Strategy & Innovation
 * Contribute to technical roadmaps, architectural decisions, and the long-term AI strategy.
 * Drive continuous improvement and innovation across the AI platform.