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Build and optimize AI/ML models for extracting structured data from unstructured documents using NLP, computer vision, and LLMs, and deploy scalable ML pipelines for high-volume processing.
Build and deploy enterprise-grade generative and agentic AI solutions end-to-end, from RAG pipelines and LLM orchestration to production monitoring and cost control, in a regulated healthcare setting.
Leads application and API security, embedding SAST/DAST tools into CI/CD, performs penetration testing, and shapes secure SDLC practices for a regulated insurance SaaS environment.
At the Mercedes-Benz company health insurance fund, we are shaping the future of digital health care, especially for the employees of the group-and you can be a decisive part of it! BE AWARE that you have to proof your…
By clicking the “Apply” button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda’s Privacy Notice…
About Cala At Cala, we’re working to free people from the burden of chronic disease. We began by creating the first non-invasive prescription therapy for hand tremor. After years of careful fine-tuning and…
About the job Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark , General Catalyst , Peter Thiel , Adam D'Angelo ,…
TL;DR: We’re looking for an AI Research Recruiter who knows where exceptional AI Researchers and engineers can be found. You’ll own full-cycle hiring across research, machine learning, data, evaluations, and ML…
Own AI-native mortgage automation tools that streamline home-buying workflows, working closely with engineers and customers to turn LLMs into reliable, mission-critical lending systems.
Build an AI-native automated testing platform using LLMs, prompt engineering, and fine-tuning to ensure software quality at every development stage.
Architects AI/GenAI product portfolios, defining target architectures, MLOps/LLMOps pipelines, and retrieval systems while ensuring Responsible AI and cost-efficient inference at scale.
Designs and owns production-ready AI and GenAI solutions, including LLMs, RAG, agentic systems, and MLOps/LLMOps pipelines, ensuring reliability, safety, and cost efficiency.
Build and maintain cloud-native backend systems and AI-driven analytics for a healthcare platform using Python, Azure/AWS, and Kubernetes.
Build and deploy RAG systems and fine-tune LLMs to generate insights about flexible workspace usage, using Python, cloud MLOps, and vector databases.
Senior Security Engineer at Arionkoder designs and implements security measures for cloud-native AWS environments, focusing on vulnerability management, SIEM tuning, and automation to reduce risk.
At River, our mission is to create personal AI owned and shaped by each individual. To achieve this, we are rewriting the entire stack from scratch: personal hardware for local inference, bespoke training…
Build and maintain AI data pipelines, ETL workflows, and integrate ML components into production systems, focusing on model inference and RAG optimization.
Build and maintain the software stack for an autonomous tile-grouting robot using ROS2, integrating AI models and embedded firmware while calibrating sensors and testing in real-world construction sites.
Build and deploy AI models: clean datasets, train neural networks, convert models to APIs, and integrate them into apps and cloud systems.
Designs autonomous network solutions for mobile/fixed telecoms using AI frameworks (Vertex AI, LangGraph), network programmability, and agentic systems to optimize performance and cost.
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