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Full-Stack Software Engineer (AI + Cloud Infrastructure)
Build a full-stack veterinary platform with React/React Native frontends, Node.js/Python backends, and AWS cloud infrastructure, integrating AI diagnostics and analytics.
Senior AI Software Engineer
Build and deploy AI-powered logistics applications in Python, integrating ML models into scalable cloud systems on AWS/Azure/GCP.
Lead AI Agents & Generative AI Architect
Lead the design and implementation of scalable GenAI, LLM, and AI-agent architectures, including RAG and MLOps/LLMOps pipelines, to deliver enterprise solutions and accelerate client adoption.
AI Architect: Generative AI, LLMs & Enterprise Systems
Designs enterprise AI systems using LLMs, NLP, and ML pipelines with TensorFlow/PyTorch, while leading MLOps and stakeholder collaboration.
Lead Data Scientist
Lead a data-science team to build and deploy ML models that turn classified datasets into operational insights for national intelligence.
Data Scientist
Build and deploy ML/AI models to extract insights and automate decisions, using Python, SQL, and cloud platforms to support business strategy.
AIML Software Engineer, AI for Science
Build cloud-native infrastructure and scalable pipelines to train and deploy large AI models for drug discovery and biomedical research using Python, PyTorch/TensorFlow, and AWS/GCP/Azure.
Machine Learning Engineer - LLMs, RAG & GenAI for Government & Public Sector
Build and deploy LLM-based AI systems for government services using RAG, fine-tuning, and prompt engineering with Python, LangChain, and cloud ML services.
AI & Data Science Consultant/Engineer (Japanese Speaking)
Design and build generative and agentic AI solutions (LLMs, RAG, agents) and data-science models for clients, then advise and demo them to stakeholders.
Data Scientist (AI / Machine Learning / Cloud)
Build and deploy production-grade AI/ML models and GenAI solutions on cloud platforms, collaborating with engineers to solve real-world business problems using Python, SQL, and modern ML frameworks.
Data Scientist (AI/ML) | Contract | Financial Services
Design and deploy AI/ML models (Generative AI, NLP, recommendations) for financial services, building scalable pipelines and driving end-to-end solutions from modeling to production.
Principal AI/ML Engineer (Computer Vision)
Lead AI/ML engineering for computer vision systems in a global supply-chain company, designing models, optimizing for production, and guiding teams to integrate vision solutions into products.
Machine Learning Engineer, Integrations
Build and integrate computer-vision models into client stacks using PyTorch, OpenCV, and Gradio; prototype cutting-edge algorithms and ship them in Datature’s MLOps platform.
Lead Machine Learning Engineer
Lead the design and delivery of end-to-end scalable machine learning systems using Python, TensorFlow, and cloud platforms, while mentoring teams and shaping ML strategy for high-stakes client projects.
Senior Data Scientist
Build and deploy ML models to forecast commodity flows and detect anomalies using geospatial and maritime data, working end-to-end from prototyping to production on AWS.
Senior Machine Learning Engineer
Design and build production-grade AI/ML platforms and MLOps pipelines for clients, using Python, cloud (GCP/AWS/Azure), Terraform, and tools like Vertex AI and Kubernetes.
Data Scientist (Geospatial)
Build and deploy geospatial ML models to forecast education demand and optimize Singapore’s long-term infrastructure planning using Python, cloud platforms, and spatial analytics.
AI Engineer (Generative AI / AI-ML / Microsoft Copilot)
Build and deploy AI-powered applications using LLMs, vector databases, and agentic AI frameworks like LangChain or Microsoft Copilot Studio for enterprise solutions.
Machine Learning Engineer
Build and deploy AI models for video analytics, including computer vision and LLMs/VLMs, to solve real-world problems across industries.
AI Engineer (Azure AI Solutions)
Design and deploy AI-powered solutions using Microsoft Azure AI services, building scalable models and integrating them into enterprise applications.