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Build and maintain ML data/model pipelines and deploy models to production for environmental, public health, and forensic challenges using MLOps tools like MLFlow and Airflow.
Lead the design and deployment of large-scale generative AI voice and speech systems, building reusable ML infrastructure and guiding cross-functional teams to integrate cutting-edge AI into products.
Build and maintain ML infrastructure to deploy and scale AI models in production, using Python, Kubernetes, and Ray. Own platform services that enable data scientists to move models from experimentation to live systems.
Leads AI/ML anomaly detection for a government financial oversight project, designing explainable models to flag fraud and waste in transaction data using Python, SQL, and Azure cloud tools.
Senior role designing and deploying AI solutions using graph data and GraphRAG for enterprise customers, from discovery to production.
Leads a team building and operating an MLOps platform and multi-agent environment, overseeing the full ML lifecycle, AI agent integration, and scalable infrastructure for a large corporation.
At ThetaRay, our purpose is to make the world a safer place by protecting the integrity of the global financial system. We do this by putting AI at the core of both our technology and our way of working. Our AI-driven…
Design and implement scalable AI systems for manufacturing, integrating predictive analytics, LLMs, and MLOps to optimize production flows and decision-making.
Build and scale Flo’s GenAI platform: LLM judges, fine-tuning pipelines, evaluation frameworks, and real-time personalization for a women’s health app used by 80M+ monthly users.
Build and train ML models that power real-time quantitative trading systems, working with PyTorch/JAX and distributed compute platforms in a fast-paced finance setting.
Build and maintain full-stack AI-native marketing platform using TypeScript, Python, and agentic coding tools like Claude Code; develop ML models, RAG pipelines, and LLM evaluation frameworks.
Build and deploy AI/ML systems for clients, working with LLMs, generative AI, and MLOps using Python, FastAPI, PyTorch, and cloud platforms.
DevOps engineer builds and maintains CI/CD, monitoring, and Kubernetes-based infrastructure for a company-wide ML platform used in decision-making, risk metrics, forecasting, and AI agents.
Build and deploy cutting-edge forecasting models and LLM agents for scenario planning in banking, using PyTorch, LangChain, and production-grade MLOps tooling.
Senior Data Engineer builds and optimizes scalable Azure-based data and ML pipelines using Databricks, PySpark, and MLOps tools to support analytics and AI deployments for fintech and public-sector clients.
Architect and build cloud-agnostic data platforms using Databricks, designing scalable pipelines and optimizing performance across AWS, Azure, and GCP for enterprise clients.
Builds Python backend services and AI agents that integrate ML models into production on embedded Linux devices, optimizing for performance and resource constraints.
Build and maintain a production-grade ML platform on Azure Databricks: automate pipelines, CI/CD, model lifecycle, and observability for thousands of time-series forecasts in HVAC.
Design and build scalable cloud data platforms using Azure, Databricks, and Microsoft Fabric, integrating governance, security, and cost controls while collaborating with engineers and analysts.
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