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Build and deploy production-grade ML models for customer segmentation, demand forecasting, and targeted campaigns in a large UK retail company undergoing AI transformation.
Build LLM-based agents and RAG systems for autonomous network operations, integrating fault diagnosis, predictive analytics, and closed-loop decision support using Python, LangChain, and vector/graph databases.
Lead AI Engineer designs, builds, and deploys enterprise-scale AI/ML and Generative AI systems, including RAG pipelines and agentic workflows, across Azure, GCP, or AWS.
Build and deploy production-grade generative AI systems for enterprise customers, coding agentic workflows and integrating them with live infrastructure using Google Cloud’s AI stack.
Build and ship end-to-end products in Python (FastAPI) and React/TypeScript, integrating AI features and deploying on GCP/AWS while owning the full stack from design to production.
Lead hands-on Data Scientist to build and launch the company’s first ML product—personalization and recommendation systems—then scale the Data Science function across e-commerce use cases like forecasting and optimization.
Design and deploy production-grade GenAI and ML solutions on AWS, optimizing cost, security, and performance while embedding reusable patterns into DoiT’s Cloud Intelligence platform.
Design and deploy production-grade GenAI and ML solutions on AWS for enterprise customers, focusing on cost efficiency, reliability, and security while creating reusable patterns and driving product adoption.
Lead multi-disciplinary programs to design and deploy Google’s data center networking infrastructure, ensuring scalable, high-availability systems powering AI/ML, Cloud, and global services.
Design verification engineer building and validating custom TPU silicon for Google’s AI/ML workloads using SystemVerilog and UVM.
Design and maintain CI/CD, IaC, and MLOps pipelines on AWS/Azure/GCP, focusing on Kubernetes, observability, and AI model deployments while enforcing DevSecOps practices.
Designs and maintains CI/CD pipelines, Kubernetes clusters, and cloud infrastructure for ML and general apps, automating deployments and monitoring systems.
Owns and scales Dialpad’s AI data infrastructure in Buenos Aires, managing BigQuery, cloud storage, Vertex AI pipelines, and Dataform to deliver clean, analytics-ready datasets for AI and product teams.
Senior Data Scientist builds, deploys, and maintains production ML models in a cloud-native environment, creating data pipelines and collaborating with engineering and business teams.
Build and maintain the AI data platform using BigQuery, Vertex AI, and Dataform; own cloud storage, IAM, and Terraform IaC to ensure reliable AI mining outputs.
Lead a cloud engineering team to design and run GCP-based AI infrastructure that ingests robotics data, trains models, and serves inference at scale for BrainOS, the platform powering 30,000+ autonomous mobile robots.
Build and deploy cloud data pipelines, model data, and integrate LLM components for clients in a consulting role.
Build and deploy cloud data pipelines, model data, and integrate LLM components for enterprise clients while auditing cloud architectures and automating deployments.
Build and optimize GCP-based data pipelines and vector databases to power AI models like LLMs and RAG systems for Doctolib’s AI Medical Companion, supporting healthcare professionals across Europe.
Builds and maintains the backend services and AI pipelines for an enterprise-grade conversational AI agent using Python, FastAPI/Flask, LangChain, and Google Gemini Enterprise on GCP.
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