Senior Applied AI Researcher (Dublin, CA)
Own and orchestrate end-to-end research programs using massively parallel agentic AI from problem formulation through production deployment, designing agent-driven experiment campaigns exploring model architectures, training regimes, data strategies, and evaluation criteria. Drive breakthrough domain-specific model quality by leading multi-stage training pipelines, domain adaptation, RL-based optimization, and training dynamics analysis, utilizing agentic systems for exhaustive ablations, hyperparameter sweeps, and failure-mode investigations. Span modalities, methods, and domains by designing and training multimodal systems, knowledge graph pipelines, hybrid retrieval architectures, and structured reasoning systems, delegating exploration and prototyping across parallel agent workflows to synthesize cross-cutting insights. Architect agentic data and training infrastructure, building agent-orchestrated pipelines for domain-specific data curation, quality filtering, preprocessing, and large-scale training. Mentor AI Researchers in the agentic paradigm, coaching team members on designing effective agent workflows to amplify their research capacities. Compress the research-to-production cycle by rapidly transitioning prototypes to production-ready systems leveraging agentic CI/CD, automated integration testing, and continuous evaluation in collaboration with engineering, product, and domain experts. Build force-multiplying knowledge systems by documenting findings, publishing at top-tier venues, contributing to internal knowledge infrastructure for indexing and reasoning by agentic tools. Continuously identify and address bottlenecks in workflows by designing or adopting efficient scalable solutions, prioritizing maximization of human potential as a core research output.
Applied AI Researcher (Dublin, CA)
Architect and orchestrate massively parallel AI research workflows by designing experiments leveraging fleets of agentic AI systems to explore hypotheses, hyperparameters, and architectural variations at scale. Design, train, and iterate on models across the GenAI stack, including LLMs, VLMs, embedding models, rerankers, and reward models, using autonomous agentic pipelines for data preprocessing, training, evaluation, and result synthesis. Conduct rigorous research into model architectures, training dynamics, reinforcement learning, and knowledge representation, accelerated by AI agents for literature review, ablation studies, and mathematical analysis. Span disciplines and modalities such as NLP, computer vision, multimodal understanding, agentic reasoning, and domain science through delegation to parallel agent systems. Develop and contribute to shared tooling, libraries, and platforms to enable researchers to orchestrate autonomous experiments, data workflows, and evaluation at scale. Collaborate with engineering, product, and domain experts to integrate research breakthroughs into production rapidly using agentic CI/CD and automated testing. Document findings, publish at top-tier venues, and build internal knowledge systems for indexing and reasoning by agentic tools to amplify collective intelligence. Identify and resolve workflow bottlenecks by designing or adopting scalable solutions to augment human potential.
Freelance n8n Workflow Developer - AI Trainer
Design, build, and evaluate advanced workflows in self-hosted n8n environments. Architect multi-system integrations for scalable automation pipelines. Develop and optimize AI-powered workflows such as content generation, automation pipelines, and enrichment systems. Build and maintain lead generation, outreach, and data processing automation systems. Implement web scraping workflows ensuring reliable data extraction and processing. Optimize workflow execution, node sequencing, and error handling to prevent failures, delays, and API timeouts.
AI Product Manager
As an AI Product Manager at Air Apps, you will define and drive the AI product roadmap ensuring alignment with business objectives and user needs. You will collaborate with cross-functional teams including engineering, design, and marketing to develop and launch AI-powered features. Conduct market research and analyze user feedback to identify opportunities for AI integration. Work closely with data scientists and machine learning engineers to optimize AI models for accuracy, performance, and user impact. Define key performance indicators (KPIs) to measure success and iterate based on data-driven insights. Stay up to date with AI trends, emerging technologies, and best practices to ensure products remain competitive. Ensure ethical AI usage and compliance with data privacy regulations.
Senior Security Operations Engineer
The Senior Security Operations Engineer is responsible for defining the internal AI roadmap in partnership with Security, Legal, and business leaders. They operate the enterprise AI stack, including LLMs, vector databases, and gateways, and enforce consistent patterns for tool calling, prompt versioning, state management, and error handling to prevent fragmented agent implementations. They manage the full model lifecycle from evaluation and testing to upgrades and deprecations. The role includes proactively interviewing internal teams to identify manual workflows for automation through agentic AI, building and deploying proofs of concept independently to demonstrate ROI before scaling, owning the token procurement process, and building forecasting and chargeback models to prevent uncontrolled spending. They also build dashboards to monitor SLAs/SLOs and usage metrics, and identify opportunities for cost-saving and performance tuning.
Forward Deployed Engineer - Strategist - Europe
As a Forward Deployed Engineer Strategist, you will work with Engineers, Product Designers, and other Strategists to deploy voice AI technology to solve customer problems. Responsibilities include meeting with strategic customers to understand their audio and voice AI needs, identifying relevant use cases through engagement with customer problems, designing and architecting custom integrations, guiding customers on best practices for AI model implementation, presenting results and proposals to technical and executive audiences, collaborating with Research and Product teams to incorporate field insights, building and delivering demos of AI technology, scoping potential applications in new industries, taking full ownership of major projects for strategic partners, and working daily with customers' engineering and executive teams to ensure optimal implementation of ElevenLabs' technologies.
Senior ML Operations (MLOps) Engineer
The Senior ML Operations (MLOps) Engineer at Eight Sleep is responsible for introducing and implementing cutting-edge ML technologies, owning the design and operation of robust ML infrastructure including scalable data, model, and deployment pipelines to ensure reliable model delivery to production. They collaborate cross-functionally with R&D, firmware, data, and backend teams to ensure reliable and scalable ML inference on Pods. They optimize ML systems for cost, scalability, and performance across training and inference, and develop tooling, microservices, and frameworks to streamline data processing, experimentation, and deployment. The role requires effective communication in a remote work environment.
Safety Engineer
The AI Safety Engineer is responsible for designing and building scalable backend infrastructure for content moderation, abuse detection, and agents guardrails by deploying AI/ML models into production systems. They will architect robust APIs, data pipelines, and service architectures to support real-time and batch moderation workflows. The role includes implementing comprehensive monitoring, alerting, and observability systems, establishing SLIs, SLOs, and performance benchmarks. The engineer will collaborate with ML engineers to translate research models into production-ready systems and integrate them across the product suite. Additionally, they will drive technical decisions and contribute to the vision for the safety roadmap to build next-generation platform guardrails for scale and precision.
Staff Product Engineer
Lead development of advanced prompt engineering and retrieval pipelines by architecting and building scalable solutions that handle thousands of customer conversations daily across integrations such as Zendesk, Intercom, and Salesforce. Leverage generation pipelines to deliver rapid insights, accurate analysis, and meaningful customer interaction scoring. Architect real-time multimodal simulations to own the development of realistic, interactive training experiences across voice, video, and chat using platforms like OpenAI, ElevenLabs, and Vapi, ensuring simulations dynamically adapt to user input for immersive learning environments. Drive high-performance user experiences by setting technical standards for intuitive, lightning-fast interfaces built with Next.js, ensuring UIs handle complex AI interactions seamlessly under demanding workloads, and mentor others to achieve similar standards.
Senior Product Engineer
Lead development of advanced prompt engineering and retrieval pipelines by architecting and building scalable solutions that handle thousands of customer conversations daily across integrations like Zendesk, Intercom, and Salesforce, leveraging cutting-edge generation pipelines for rapid insights, accurate analysis, and meaningful customer interaction scoring. Architect real-time multimodal simulations by owning the development of realistic, interactive training experiences across voice, video, and chat using platforms like OpenAI, ElevenLabs, and Vapi, with simulations dynamically adapting to user input to create immersive learning environments. Drive high-performance user experiences by setting technical standards for intuitive, fast interfaces built with Next.js, ensuring UIs handle complex AI interactions seamlessly under demanding workloads, and mentoring other engineers to achieve the same technical standards. Shape technical decisions, own major parts of the product, mentor teammates, and push personal skills in full-stack development including frontend, backend, and AI integrations, making critical decisions about architecture, tooling, and product direction.
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