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Build and scale Generative AI features for Google Workspace products like Gmail and Docs. The role involves full-stack software development, design reviews, and debugging, heavily leveraging ML infrastructure, LLMs, and multi-modal vision models to impact billions of users.
Senior Data Scientist at a healthcare AI startup building a clinical foundation model; designs, curates, and analyzes complex healthcare datasets (EHR, claims) to power AI models and improve patient outcomes.
Description Data Scientist/ Forward Deployed Engineer Overview Join a newly formed, executive-sponsored AI Transformation team focused on bringing AI solutions from concept to production across a large enterprise…
True Zero Technologies, a veteran-owned small business, was founded on the principle that the purposeful enablement of people and technology in an organization directly ties to the quality of its outcomes. True Zero…
Develops GenAI-powered content understanding and generation frameworks for Google Search, integrating cutting-edge AI models into scalable systems to enhance content retrieval and user experiences across platforms.
Senior Software Engineer in Google's Labs incubation group, building and deploying ML/AI solutions—including generative AI, ML infrastructure, speech/audio, or reinforcement learning—at scale across Google's products.
Deepgram is seeking a Software Test Engineer to design and maintain automated test frameworks and evaluation pipelines for their voice AI platform. The role involves building scalable testing infrastructure, validating model performance, and ensuring the reliability of APIs and data workflows.
As a Staff Software Engineer for AutoCloud, you will lead the architecture of AI-powered memory and context systems for autonomous cloud management. You will design scalable, low-latency infrastructure for agent memory, RAG platforms, and cloud state aggregation while collaborating with research teams.
Embedded AI engineer at Google Cloud who builds, deploys, and optimizes production-grade agentic AI systems for enterprise customers, bridging Google’s AI products with client infrastructure while feeding insights back to product teams.
The Product Owner for an AI Email App defines AI capabilities and system behavior to enhance user workflows with minimal prompting, focusing on reliability, context, and real-world task completion. They collaborate with ML and engineering teams to balance quality, latency, cost, and UX while ensuring predictable, trustworthy AI interactions.
Technical Product Manager defining end-to-end requirements for LLM-based AI systems, working closely with ML and engineering teams on system design, evaluation frameworks, and product quality in a zero-to-one startup environment.
Data Scientist builds ML models to assess credit, market, and fraud risks for a major Ukrainian bank, using Python, SQL, and cloud tools like SageMaker.
The Senior Data Scientist will build machine learning models and perform causal analysis to understand customer value, behavior, and segmentation for client engagements. The role requires strong Python and SQL skills to translate complex data into actionable business recommendations.
Lead a team of AI engineers in Gurgaon to design, build, and deploy production-grade GenAI and agentic AI solutions on GCP and Azure, ensuring scalability, security, and measurable business impact for global retail and brand clients.
Build and scale production AI systems for English Language Learning, developing agentic content generation workflows and LLM-powered services (Conversation Brain, Ambient ORA) that serve multiple Pearson products. Work with Python (FastAPI, CrewAI, LangGraph, LangChain), Azure, and observability tools to operationalize AI from research into production.
The AI Engineer will integrate AI/ML models and LLM-based applications into production systems while collaborating with data scientists to operationalize pipelines. The role involves building end-to-end Gen AI solutions and maintaining automated CI/CD pipelines.
Hands-on technical leadership role designing and delivering production-grade Generative AI and Agentic AI solutions, including LLM-powered applications, RAG pipelines, multi-agent architectures, and LLMOps using Python, agent frameworks, and cloud platforms.
Build and maintain AI/ML systems for robotics, including training evaluation pipelines, model fine-tuning, deploying algorithms in simulation and on physical hardware, and integrating robotic control and perception stacks.
Design, develop, and deploy NLP/LLM-based production systems using Python, PyTorch, and frameworks like LangChain for Hudhud's geospatial and location-intelligence platforms.
The Lead Data Scientist will define evaluation frameworks and measurement strategies for Strava's AI-driven data products. This role involves partnering with machine learning engineers to ensure model quality and performance across the platform.
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