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Lead the design, training, and deployment of production-grade ML models in Python for high-growth clients, using cloud infrastructure and MLOps tooling to drive business decisions.
Build and deploy ML models and MLOps pipelines using Python, TensorFlow/PyTorch, and cloud platforms like Azure Databricks for real-time data-driven solutions.
Builds and deploys ML models (deep learning, MLOps) for clients across industries, using Python/TensorFlow/PyTorch, Kafka, and cloud platforms like Databricks/Fabric, while collaborating with cross-functional teams to deliver scalable, real-time data-driven solutions.
Build and maintain the MLOps platform that lets Oura’s data-science teams train, deploy, and monitor ML models reliably at scale in AWS.
Build and ship production-grade LLM systems, RAG pipelines, and agentic workflows on Databricks, optimizing for latency, cost, and reliability while mentoring peers.
Build and deploy AI/ML models (LLMs, NLP, deep learning) for client projects, from requirements to production, using Python, SQL, and cloud tools (AWS/GCP/Azure).
Senior ML Engineer at Doctolib builds and deploys AI systems (LLMs, retrieval pipelines, agentic AI) to improve patient access to healthcare, using Python, vector databases, and cloud-native tools.
Build and maintain secure ML pipelines for healthcare data, including LLM and custom model deployment, anonymization, and threat detection in production.
What we do At Doctolib, we are building AI-powered healthcare solutions that make a real difference in the lives of millions of patients and healthcare professionals every day. Our AI organization is at the heart of…
Build and maintain AWS-based MLOps platforms for GenAI models, automating pipelines with SageMaker, MLflow, and CI/CD while ensuring secure, scalable deployments.
Leads a team of ML engineers and data scientists to design, deploy, and maintain machine learning systems for sports betting and gaming platforms using Python, TensorFlow/PyTorch, and AWS.
Senior Engineer builds and maintains a scalable ML platform for real-time data processing, model deployment, and monitoring, enabling AI adoption across teams using Python, cloud services, and Kubernetes.
Leads machine learning initiatives for an online gaming platform, designing and deploying scalable models to enhance security, user experience, and data-driven decisions for hundreds of thousands of users.
Senior AI Engineer builds and deploys ML models (including LLMs) and end-to-end AI solutions for enterprise clients, focusing on MLOps, software engineering, and translating business problems into measurable outcomes.
Build and run the ML platform that trains, serves, monitors, and retires models in batch and real-time on CPU/GPU, using Kubernetes, Triton, MLflow, Prometheus and CI/CD.
Our mission is to transform how people and machines work together to push the boundaries of human productivity. A leader in Industrial AI, Augury helps the world’s manufacturers leverage real-time production insights…
Builds and deploys ML ranking and recommendation models to personalize search results for millions of users on Avito’s classifieds platform.
Lead AI/ML strategy and teams at early-stage startups, defining product roadmaps and deploying generative AI systems using Python, PyTorch, and cloud MLOps stacks.
Principal AI/ML Engineer to architect and deploy cutting-edge models (LLMs, transformers) and lead AI strategy at high-growth startups in SignalFire’s portfolio.
Build and deploy AI models from scratch for early-stage startups, leading RAG pipelines, agent architectures, and LLM-powered systems in Python with PyTorch/TensorFlow.
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