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Designs and builds enterprise AI/ML solutions using deep learning and GenAI, deploys scalable pipelines, and leads end-to-end projects from data assessment to production.
Build and scale the ML infrastructure that powers Nearmap’s aerial imagery and AI-driven property analytics, including batch inference, real-time model serving, and LLM platforms on AWS/GCP.
Build and scale the ML infrastructure that powers Nearmap’s aerial-imagery AI, including EKS batch inference, Ray Serve real-time serving, and GPU training on AWS/GCP.
Build and deploy ML models to detect fraud and improve customer experience in a global digital gifting and payments platform.
Senior ML engineer building perception systems for autonomous maritime robots using computer vision, sensor fusion, and real-time ML pipelines.
Build and deploy production-grade ML models and pipelines to improve pet healthcare outcomes using Python, cloud platforms, and modern AI practices.
Build and deploy ML models to detect fraud and improve customer experience in digital gifting and payments, using frameworks like PyTorch and cloud platforms such as AWS.
Lead a team of AI/ML scientists at a global lifestyle brand, setting technical direction, designing new algorithms, and delivering rigorous AI solutions that drive measurable business impact.
Build and deploy scalable AI/ML systems, including LLM pipelines, RAG, and MLOps tooling, to production for a global lifestyle brand.
Design and build automated data-labelling pipelines using Active Learning, Weak Supervision, and Synthetic Data to reduce manual annotation and feed ML models.
Build and deploy AI systems including LLMs, computer vision, and autonomous agents using Python, PyTorch, and LangChain, then productionize them with MLOps on cloud platforms.
Build and optimize GenAI systems using LLMs, prompt engineering, RAG, and agent workflows with frameworks like LangChain. Integrate APIs, vector databases, and external tools for scalable AI solutions.
Build and scale AI agents and ML pipelines using Python, PyTorch/TensorFlow, and frameworks like LangChain; integrate LLMs, vector DBs, and cloud-native systems.
Build and deploy AI-powered applications using LLMs, RAG pipelines, and vector search. Integrate LLM APIs into production systems with Python and cloud tools.
Build and deploy ML pipelines and LLM services for a healthcare AI platform that supports population health and clinical decision-making.
Design and scale a cloud-native data and AI platform, building real-time analytics, industrial data pipelines, and AI/ML infrastructure across AWS and on-prem.
Build and deploy ML models for a sales-enablement platform, collaborating with data science and product teams to improve model performance and scalability.
Builds core backend services in Python and PostgreSQL, collaborates with frontend teams, and ships product features in a fast-paced AI-focused company.
Build and maintain .NET backend services and AI/ML features for a real-estate platform, including gRPC APIs, vector search, and LLM-powered personalization integrated with SQL Server, MongoDB, and Elasticsearch.
Build and fine-tune LLMs and NLP pipelines for an AI-powered language-learning platform, integrating agentic workflows and model-serving tools.
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