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Build and deploy AI-driven applications using Python, LLMs, and vector databases to automate IT operations and provide insights for a government contractor.
Build and deploy NLP models and AI pipelines for a chatbot program, integrating with cloud services and collaborating with cross-functional teams.
Build, deploy, and maintain AI/ML models on GCP for a defense program, focusing on LLMs, RAG, and Agentic AI while ensuring secure, scalable production systems.
Build and deploy production-grade ML systems for personalization, search, and generative AI at Autodesk, using Python and frameworks like PyTorch or TensorFlow.
Builds and deploys on-device AI prototypes using C++/Python, PyTorch, and low-level system tools for edge devices like smartphones and IoT.
Optimize and deploy AI models on Qualcomm’s chipsets to maximize inference efficiency and accuracy using C/C++ and Linux/Android environments.
Research and develop efficient on-device AI inference systems, focusing on model compression, hardware-software co-design, and optimization for Qualcomm’s low-power AI accelerators.
Senior engineer optimizing ML model deployment and performance on embedded AI hardware for autonomous vehicles, using C++, CUDA, and TensorRT in a Linux environment.
Build full-stack AI applications integrating LLMs and ML models into production systems using Python, TypeScript, and cloud platforms.
Design, build, and deploy AI and data science solutions for government clients, including ML models, pipelines, and analytics products using Python, SQL, and cloud platforms.
Build and maintain Kubernetes-based infrastructure on AWS and on-premises to support AI workloads, data pipelines, and ML operations for an AI-driven energy-management platform.
Builds and deploys advanced ML models (e.g., neural retrieval, clustering, ranking) to personalize Google Search and Discover, optimizing user engagement at global scale with realtime systems.
Czym będziesz się zajmować? Project scope: Write production-ready code and use GPU or CPU resources according to ML workload capacity needs. Architect, automate and orchestrate cloud DevOps and MLOps pipelines. Create…
Build and deploy production-grade generative AI systems using Python, LLMs, RAG pipelines, and AWS services like SageMaker and Bedrock.
Build and own data pipelines, warehousing, and ML infrastructure for an AI-powered workforce development platform, transforming labor market and skills data into job-matching systems using Python, SQL, Airflow, dbt, and AWS.
Designs and governs enterprise AI systems, including LLMs and MLOps, ensuring scalable, secure, and compliant solutions aligned with business goals.
Maintains and expands industrial data-historian systems (AVEVA PI/IP.21), curates clean datasets, and prepares AI-ready data pipelines for renewable-energy monitoring and predictive analytics.
Build and deploy ML models that power travel-management features, collaborating with data analysts and engineers to turn business KPIs into production-ready AI systems.
Builds scalable data pipelines and AI/ML models in Python/SQL, deploys them to cloud, and maintains MLOps workflows using Spark, TensorFlow, and Airflow.
Maintain and automate SAS Viya environments for ING’s modelling teams, deploy risk models, and troubleshoot platform issues while collaborating with DevOps and cloud teams.
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