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Lead AI Engineer — Generative AI & Data Science (Remote)
Lead a team building generative AI and data-science solutions using Python, LLMOps, and cloud services; design multi-agent patterns, reasoning loops, and scalable microservices.
AI Engineer (Generative AI & Data Science Solutions)
Design and build generative AI and data-science solutions using Python, TensorFlow/PyTorch, and LangChain, then deploy them as scalable microservices on AWS/GCP/Azure.
Lead AI Engineer (Generative AI & Data Science Solutions)
Lead a team to design and build generative AI and data-science solutions using Python, TensorFlow/PyTorch, LangChain, and cloud services, while overseeing MLOps, microservices, and CI/CD pipelines.
Lead AI Engineer (Generative AI & Data Science Solutions)
Lead AI Engineer designing and implementing generative AI and data-science solutions, including multi-agent systems, reasoning loops, and MLOps tooling in Python/Java with cloud providers.
Data Scientist / ML Engineer
Build and deploy ML models to optimize ad targeting and bid strategies for a mobile-app monetization platform using Python, PyTorch, and AWS.
Data Scientist / IA Engineer
Build and deploy ML models, LLMs, and AI agents using Python, MLOps, and cloud platforms (Azure/AWS) for enterprise clients.
Data Engineer – Clinical Trials
Build and maintain scalable data pipelines and ML systems for clinical trials, turning raw data into production-grade solutions that support trial design, patient recruitment, and real-time monitoring.
Data Engineer MLE
Build and maintain scalable data pipelines and production-grade ML systems for clinical trials, pharmacovigilance, and drug manufacturing at a global pharma company.
Data Engineer
Build and run the AIOps platform that keeps AI models, LLM pipelines, and agents reliable, scalable, and cost-efficient in AWS/Azure.
Data Engineer
Build and maintain data pipelines and warehouses for AI projects, using PySpark, Databricks, and Azure services to centralize and process large datasets.
Principal Full Stack ML Engineer – Evinova
Build and deploy ML models and agentic systems to improve clinical trial success rates using Python, FastAPI, TensorFlow/PyTorch, and AWS.
Full Stack Engineer, AI systems
Builds AI-native workflows and agent systems that handle multi-step tasks, integrating LLMs, memory, and external tools into reliable, production-grade features.
AI Full Stack Engineer
Build and deploy production-grade AI systems end-to-end, from data pipelines and ML models to scalable deployment and monitoring using Python, PyTorch, and MLOps tools.
Full Stack Developer (web)
Senior full-stack developer building and maintaining web apps, handling front-end, back-end, DevOps, and cloud deployments with modern stacks and AI integrations.
Full Stack Developer (web)
Build and maintain full-stack web apps using TypeScript, Node.js, React, and cloud services (AWS/GCP/Azure), while integrating AI libraries and LLM APIs in a fast-paced product team.
Backend Developer
Build and deploy AI-driven data analytics and generative AI solutions on Azure and GCP, including MLOps pipelines and agentic AI workflows.
Senior Software Engineer, Systems ML - AI Application Engineering
Build and optimize Meta’s AI systems by applying deep expertise in ML infrastructure and hardware acceleration to enhance product experiences.
Data Science / ML Engineer
Build and deploy ML models and MLOps pipelines using Python, TensorFlow/PyTorch, and cloud platforms like Azure Databricks for real-time, event-driven data solutions across industries.
Data Engineer: Build the data foundation for the future of care
Build and maintain data pipelines in Python, C# and .NET that turn sensor, alarm and activity data into reliable datasets for AI-powered care products like Sensio Insight.
Data Science / ML Engineer
Build and deploy ML models and MLOps pipelines for public-sector clients using Python, TensorFlow/PyTorch, Kafka, and Databricks.