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Full Stack Web Developer
Build and scale a platform to deliver machine-learning model results for chemical datasets, collaborating with ML engineers on backend services, APIs, and full-stack development.
Cloud Platform Engineer
Build and run the cloud infrastructure that serves SambaNova’s AI inferencing endpoints, ensuring high availability, low latency, and cost-efficient scaling across AWS, GCP, Azure, and on-prem.
Senior Software Engineer, ML Data Delivery (Remote)
Build and maintain ML data pipelines for autonomous trucking, curating high-quality sensor annotations and delivering on-demand training data to perception models.
Senior Machine Learning Engineer, 3D Reconstruction (Remote)
Build and deploy ML models for 3D scene reconstruction, lane detection, and HD map creation using LiDAR/camera data to generate high-quality annotations for autonomous trucking systems.
Data & AI Engineer
Design, build, and deploy enterprise-scale AI/ML solutions using Python, SQL, and frameworks like TensorFlow/PyTorch, with cloud deployment on Azure/AWS/GCP.
Lead data scientist, fraud modelling
Lead a fraud-detection team building ML models to protect an affiliate-marketing platform from attribution fraud, lead fraud, and emerging threats like browser-extension abuse.
Ai engineer
Design, develop, and deploy AI/ML models, generative AI apps, and intelligent agents using Python, TensorFlow, and PyTorch in cloud environments.
Data Science & AI Lead
Lead AI and machine learning initiatives, building predictive models and GenAI/LLM solutions to drive retail and FMCG insights and automation.
AI Engineer, Asia (12 months contract)
Builds and deploys GenAI applications using LLMs, fine-tuning models, and integrating MLOps pipelines for production systems like chatbots and document analyzers.
Data Scientist (Manager/Senior Manager)
Lead AI/ML projects for EY’s clients, designing and deploying GenAI models (LLMs, vector DBs) and traditional ML solutions using Python, cloud platforms, and MLOps pipelines.
Data Science & GenAI Lead: Build Predictive Engines
Lead predictive modeling and GenAI initiatives, building churn/LTV models and LLM-powered tools while setting evaluation standards and driving business adoption.
Machine Learning Operations Engineer
Build and operate production-grade ML pipelines on Databricks, implementing MLOps practices like CI/CD, model monitoring, and secure deployment while collaborating with data science and engineering teams.
Machine Learning Operations
Build and deploy AI/ML pipelines for a large bank, integrating traditional, generative, and agentic AI into production using OpenShift, Kubernetes, and AWS while automating DevOps workflows.
AI Engineer
Designs, builds, and deploys generative AI models and MLOps pipelines for a bank’s digital platforms, integrating NLP and multi-modal systems while ensuring governance and regulatory compliance.
Senior Data Scientist — AI, ML & Data Engineering
Design, build, and deploy scalable AI/ML systems in Kuala Lumpur, owning the full lifecycle from data prep to production monitoring and continuous improvement.
DATA SCIENCE & AI LEAD
Lead the build-out of predictive models (churn, LTV, demand) and GenAI tools (RAG, copilots) for a retail/FMCG business, then translate outputs into actionable business recommendations.
Data Scientist (Mid / Senior) — AI, Machine Learning & Data Engineering
Design, build, and deploy AI/ML models and scalable data pipelines for predictive analytics and business optimization using cloud and MLOps practices.
AI Engineer/ Architect- 12 months- 6k$- Insurer- No visa
Architect and implement enterprise AI solutions for an insurer, focusing on Generative AI, LLMs, and cloud-native platforms to modernize underwriting, claims, and customer service.
Lead/Senior AI/ML Engineer, R&D – Computer Vision (m/f/d)
Lead AI/ML engineering for medical imaging: build, evaluate, and deploy deep-learning models for segmentation, detection, and classification across dental radiographs and CBCT data.
Senior AI/MLOps Engineer for Production-Scale ML
Engineers and deploys production-grade AI/ML systems using MLOps practices on Azure, managing model lifecycle, CI/CD, and monitoring for scalable, secure deployments.