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Build and deploy AI/ML models (LLMs to classic regression) and shape the company’s GenAI strategy while bridging Data Science and MLOps in a fast-paced fintech environment.
Build and maintain scalable data pipelines and cloud-native infrastructure to ingest and optimize multi-modal scientific datasets for ML model training in drug discovery.
Build and optimize cloud-native data pipelines and lakehouse infrastructure to process multi-omics datasets for ML-driven drug discovery in a TechBio company.
Build and maintain scalable data pipelines and AI-driven systems for an ethical ad-tech platform, integrating ML models into production while ensuring data quality and security.
Principal Data Engineer designs and maintains secure, scalable data platforms and pipelines for Defence/Aerospace programmes, using cloud-native tech and DataOps to enable analytics and digital transformation in regulated environments.
Build and maintain cloud-native MLOps and data pipelines for a biotech firm, deploying and scaling ML models in AWS/GCP while ensuring reliability, security, and reproducibility.
Senior MLOps & Data Engineer builds and maintains cloud-based AI infrastructure on AWS/GCP, deploys ML models, and creates data pipelines for a biotech company.
Design, build, and deploy enterprise-scale AI/ML solutions using Python, SQL, and frameworks like TensorFlow/PyTorch across Azure, AWS, or GCP.
Build and maintain Snowflake-based data platforms and automated pipelines to power analytics, AI, and ML workloads for a UK insurance company.
Lead AI Data Engineer builds and optimizes RAG pipelines, fine-tunes LLMs, and designs secure data ingestion systems for a proptech company serving insurance and banking clients.
Lead AI/ML Data Engineer builds and deploys machine-learning features and data pipelines for Mastercard’s products, using Python, Spark, and cloud platforms.
Build and deploy Azure-based machine learning models using Python and AutoML, then monitor and retrain them to keep them accurate and ethical in production.
Build and maintain scalable data pipelines using Azure technologies and Databricks to help clients extract value from their data assets.
Build secure, scalable data pipelines and AI-ready platforms for Defence customers using Python, Kafka, Spark, and Kubernetes in air-gapped environments.
Build high-performance distributed systems in Python (with Rust/Go exposure) for a FinTech firm handling multi-petabytes of data and a new greenfield ML platform.
Build cloud-based microservices for an AI-driven SaaS platform using Python, AWS, REST APIs, and MLOps, collaborating with ML engineers to ship scalable features.
Build and deploy AI/ML models and generative AI systems for government clients, focusing on scalable MLOps pipelines, cloud deployments, and integration with Army operations.
Set the reliability strategy for Yuno’s AI-native payments platform on AWS, designing event-driven messaging, SLOs, and chaos engineering to keep global AI agents and payment flows running 24/7.
Build and optimize AI-driven simulation models for engineering and manufacturing, scaling deep learning and distributed training across cloud and on-premise systems.
Senior engineer building and scaling cloud-native AI platforms, automating MLOps/LLMOps pipelines, and containerizing workloads with Kubernetes and FastAPI.
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