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Build and automate end-to-end ML pipelines for retail analytics and forecasting, integrating Oracle, Snowflake, and AWS with Kedro, MLflow, and Docker.
Build and deploy GenAI/NLP pipelines for Elsevier’s life-science products, orchestrating ML workflows on AWS/Azure, managing vector/graph search, and enforcing content rights and confidentiality.
Build and deploy computer-vision models using deep learning frameworks like PyTorch/TensorFlow to classify images, detect objects, and segment scenes for AI applications.
As an Applied Scientist II specializing in lead scoring and deep learning modeling, you will build and improve machine learning models that power how our business engages with customers. You will develop predictive…
Design, build, and deploy ML models and AI systems for a global talent marketplace, spanning data prep to production monitoring using Python, TensorFlow/PyTorch, and MLOps tooling.
About the Role We are looking for a Python Software Engineer to join our engineering team and work at the intersection of software development, machine learning, and embedded systems. The primary focus of this role is…
Design and build enterprise-grade MLOps platforms to automate the full ML lifecycle from data prep to retraining and governance using cloud-native tools like Kubernetes, CI/CD, and IaC.
Build and optimize Databricks-based lakehouse pipelines, including Delta Live Tables, ETL/ELT, streaming ingestion, and ML-ready datasets with MLflow and Unity Catalog.
inviol is one of New Zealand's fastest-growing startups, on a mission to save lives by turning AI insights into safer worksites. We plug into the CCTV cameras a business already has, spot the risky moments no one…
Build and scale the cloud and AI infrastructure for a Zero Trust security platform, including Kubernetes, CI/CD, observability, and MLOps tooling while mentoring engineers to own the platform long-term.
Build and deploy ML models using Python, TensorFlow/PyTorch, and cloud tools; engineer features, optimize pipelines, and productionize AI systems with MLOps.
Senior Machine Learning Engineer builds and deploys LLM-based AI systems, including agents and multimodal workflows, using Python, AWS, and CI/CD in a fast-paced consulting environment.
Builds and maintains ML data pipelines for autonomous truck perception models, curating high-quality sensor annotations and delivering data for on-demand model training.
Build and deploy ML models for dynamic pricing, demand forecasting, and routing in a global ride-hailing SaaS platform using Python, SQL, Kubeflow, and MLflow.
Build and maintain the AI platform and data lakehouse, automating operations and deploying services using Python, Kubernetes, and MLOps tools.
Build production-grade AI systems and data pipelines end-to-end, owning schema design, ETL, FastAPI/Next.js apps, and cloud deployments on AWS/Azure.
Build and automate predictive models and ETL pipelines on Databricks/Azure to power Awin’s adtech reporting and campaign optimization, using Python, PySpark, and ML frameworks.
Builds open-source data platforms using Python and Kubernetes, integrating ML tools like Kubeflow and MLFlow for cloud and private infrastructure.
Build and deploy AI models for human-like conversations, spanning speech, language, and real-time inference systems. Own end-to-end ML pipelines and MLOps tooling in a fast-moving startup.
Build and ship AI-native financial-data products, including LLMs and agentic systems, to unify and reconcile market data for investment portfolios.
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