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Design, build, and deploy scalable generative AI and MLOps pipelines for enterprise systems, collaborating with data engineers and product teams.
Lead AI/ML modeling to uncover sales opportunities and build predictive tools for revenue forecasting and pricing decisions using Python, SQL, and ML frameworks.
Senior ML engineer builds multimodal medical imaging AI systems—foundation models, report generation, lesion detection—using Python/PyTorch and collaborates with clinicians to deploy in hospitals.
Build and optimize speech AI models (ASR, diarization) and pipelines, deploy ML services, and improve accuracy/latency for production systems.
Build and deploy scalable speech AI systems, training and optimizing ASR, diarization, and analytics models using PyTorch and modern ML toolkits.
Build and optimize speech AI models (ASR, diarization) for medical applications, including data pipelines, training, and inference in Python/PyTorch.
Build and deploy ML pipelines and models for cybersecurity products, focusing on MLOps and production-scale AI systems.
Senior ML Engineer builds real-time AI systems for games, including LLM-driven NPCs and adaptive environments, using C++/Python and Unreal Engine.
Senior ML Engineer builds and deploys transformer-based NLP models to auto-score exam answers, owning the full lifecycle from training to cloud deployment and bias mitigation.
Builds scalable backend services for a real-time AI/ML platform using Java/Spring Boot, RESTful/GraphQL APIs, and cloud infrastructure.
Build and operate CI/CD pipelines and AI-enabled tooling for a platform that helps job seekers and employers match efficiently.
Design and deploy ML systems and predictive models using Azure MLOps and NLP for client projects.
Build AI/ML systems for Grab’s food-delivery platform, including demand shaping, content enrichment, and generative AI features to improve user experience and platform efficiency.
Designs and automates MLOps and DevOps pipelines for scalable AI/ML platforms, ensuring secure, reliable model training and inference workflows across multi-cloud and on-premises environments.
Build and optimize AI applications and MLOps pipelines using Python, LLMs, and cloud platforms while collaborating with data scientists and architects.
Build and productionise ML models for an e-commerce platform, using Python, TensorFlow/PyTorch, and cloud pipelines to improve product recommendations and business decisions.
Design and build scalable agentic AI systems using GenAI, vector embeddings, and cloud infrastructure for enterprise solutions.
Senior ML Engineer trains AI models by creating reasoning traces for complex tasks, documenting planning and decision-making processes, and guiding LLMs through real-world decisions.
Build and scale the ML infrastructure that powers Nearmap’s aerial imagery AI products, including real-time model serving, distributed training, and LLM platforms on AWS/GCP.
Build and scale the ML platform that powers Nearmap’s aerial imagery analytics and generative AI products, running on AWS/GCP with Kubernetes, Ray Serve, and GPU workloads.
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