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The AI Architect will design and implement enterprise-grade AI, Machine Learning, and Generative AI solutions while leading technical teams on complex automation projects.
Build and operate Kubernetes-based platforms for AI Co-Workers, using Terraform and Helm to deploy resilient, scalable AI workloads with strong observability.
Slang.ai is seeking a Senior Product Manager II to lead product strategy and execution for their voice AI platform. The role involves managing product lifecycles, collaborating with engineering and design, and utilizing AI tools to improve restaurant customer service interactions.
The Robotics Test Engineer will build automated test frameworks and hardware-in-the-loop systems to validate the performance and reliability of generalist intelligent robots. This role involves working across hardware, firmware, and software to identify and resolve complex system failures.
This role involves designing and building multi-agent AI systems and the supporting infrastructure for a med-tech company. The engineer will work with LLMs, the MCP protocol, and cloud infrastructure including EKS and Terraform while utilizing Java and React.
Develops software tools for multi-agent UAV autonomy, bridging simulation and real-world deployment to enable defense customers to design, train, and validate coordinated drone missions. Core tech: autonomy algorithms, reinforcement learning, UAS development, and cross-team collaboration with US-based product engineering.
Build and deploy AI/ML models for autonomous truck software, from data pipelines to embedded deployment, while exploring cutting-edge initiatives.
Design and build training and assessment modules for annotator onboarding and screening at an AI data platform, applying learning science and production performance data to establish instructional methodology from scratch.
Senior backend-focused full-stack engineer building neuro-symbolic AI applications for tax professionals, owning data models, execution engines, and production reliability at a hybrid San Francisco AI company.
Lead enterprise-scale GenAI implementations for Fortune 500 clients, designing and building production-grade LLM, RAG, and agent-based systems using Python, cloud platforms (AWS/Azure/GCP), and frameworks like LangChain.
Build and deploy AI-enabled tools and platforms for SEEK, embedding copilots and agents into workflows to improve productivity and decision-making across teams.
Design and own production-grade AI agent infrastructure across multiple cloud providers (Azure, Oracle Cloud, GCP, AWS) using Kubernetes, Terraform, and CI/CD automation at an early-stage AI startup.
Designs and maintains scalable Azure-based data pipelines and platforms for government datasets, enabling AI/ML and analytics. Builds ETL/ELT workflows using tools like ADF, Databricks, Spark, Kafka, and SQL, collaborating with data scientists and MLOps teams.
Build and deploy enterprise-grade GenAI applications using Dataiku, including chatbots, RAG systems, SQL agents, and AI-driven reporting with custom web apps.
Manages hybrid Dataiku infrastructure (on-prem RHEL + Azure AKS GPU clusters) for AI model training/inference, overseeing security, automation, and performance monitoring.
Builds and maintains data pipelines using Python, SQL, Spark, and Kafka to extract, transform, and load data for AI/ML integration and cloud-based analytics.
Builds and deploys AI/ML applications using Snowflake Cortex, LLM APIs, and Python frameworks to integrate GenAI into enterprise data ecosystems, focusing on vector search, agentic workflows, and real-time analytics.
Design and develop GenAI-powered integrations and connectors (Microsoft Copilot, Google Gemini, Claude, OpenAI) for enterprise use cases, implementing MCP and agent-based communication patterns using Python.
Leads AI/ML projects from ideation to production, specializing in LLM/Agentic AI development, cloud-based model deployment, and MLOps best practices for fintech applications.
Build and optimize AI/ML models for computer vision tasks using TensorFlow/PyTorch, deploying scalable solutions on AWS with CI/CD pipelines.
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