Senior Software Engineer, AI Voice Agent
As a Senior Software Engineer on the AI Voice Agent team, you will work on real-time systems involving live audio streaming and latency optimization integrated with speech providers. You will build and improve conversation intelligence systems that manage LLM layers, including prompt construction, context management, function calling, and dialogue management to create natural, actionable phone conversations. You will develop the action framework allowing configurable API calls with branching logic and runtime execution, supporting tasks like data lookup and ticket creation during calls. You'll manage knowledge ingestion, storage, and retrieval to enhance agent memory and learning over time. You will collaborate with designers to enable customers to create, configure, test, and deploy voice agents through intuitive product experiences. Additionally, you will help develop evaluation frameworks, analytics, call quality metrics, and monitoring instrumentation, and participate in on-call rotation duties.
Deployment Lead
The Deployment Lead will work closely with Simulation Engineers, Machine Learning Engineers, and customers to understand and define engineering and physics challenges, providing technical leadership to their team. Responsibilities include leading pre-processing and analysis of complex data for predictive modelling, establishing best practices, architecting and developing innovative deep learning models combined with optimisation methods, taking responsibility for the quality and impact of their work and their team's work, designing and testing robust, scalable data pipelines for production environments, leading cross-functional collaboration for seamless integration of data science models with simulations, driving internal R&D and product development to refine models and identify new applications, mentoring junior team members, leading communication and presentations to technical teams and customers, onboarding users and co-developing solutions with customers. The role involves representing the company as a technical authority at customer sites internationally, collaborating on-site to build solutions, influencing technical direction, shaping future solutions and products, and developing leadership skills.
Member of Technical Staff (Data): World Models
Design, automate, maintain, and optimize Python ETL pipelines (Spark/Ray) for large-scale multimodal data. Build and maintain data cataloging, lineage, quality tooling, integrity verification, access controls, and lifecycle management systems. Provide guidance, internal tools, and documentation to colleagues on data best practices. Serve as a custodian of the company’s datasets, ensuring overall data health, quality, and discoverability.
AI Product Engineer (Agents)
Build LLM agents for document understanding, search, and image recognition that transition quickly from prototype to production; write clean, tested Python code that scales, focusing on working AI features rather than research papers; collaborate with AI and product teams to iterate on solutions that customers actually use; manage multiple projects with high ownership using LangGraph and cutting-edge AI frameworks; build agents, tune models, and ship AI solutions that power the entire platform.
Forward Deployed Engineer
Run technical discovery, design solutions, and lead POCs alongside Account Executives to close deals, then own onboarding to get customers to first value fast. Build and implement workflows within V7 Go; combining prompt engineering, data pipelines, and integrations to solve real customer problems across document processing and more. Act as the primary technical contact for accounts, handling complex challenges and spotting expansion opportunities as customers scale. Juggle up to 10 concurrent projects while feeding customer insights back to product and engineering.
Enterprise Account Executive, EMEA
Build new LLM and instrumentation libraries for emerging LLM providers and agent frameworks. Maintain and enhance existing instrumentation across Python and TypeScript ecosystems and others such as OpenAI, Anthropic, LlamaIndex, CrewAI and more. Drive improvements to semantic conventions and OpenTelemetry standards that define AI observability. Collaborate with the global developer community through GitHub, Slack, and conferences, as well as with Arize PMs and solution architects. Take complex problems from ideation to completion with full ownership and accountability.
Senior Machine Learning Scientist
The Senior Machine Learning Scientist will train, evaluate, and iterate on ML models and agentic systems for customer feedback, including owning custom fine-tuning pipelines. They will run experiments end-to-end, track results rigorously, and make recommendations on what to ship, iterate, or retire. The role involves building and maintaining LLM-powered features such as retrieval pipelines, reranking systems, insight agents, data mining agents, and automated taxonomy generation. The scientist will design and run robust evaluation frameworks including building test sets, defining metrics, evaluating non-deterministic systems, handling class imbalance, and automating checkpoint comparisons. They will improve and extend semantic search and retrieval methods, write production-quality code, and collaborate closely with Engineering on productionisation, model serving, data pipelines, and monitoring. The role includes working with Product and Commercial teams to translate business needs into practical ML solutions and supporting client evaluations and accuracy benchmarking. Additionally, the scientist will mentor team members, review code and research, and integrate relevant advances from literature into the product.
Sales Enablement Systems Lead
The Sales Enablement Systems Lead is responsible for reinventing how ElevenLabs manages, organizes, and delivers internal knowledge to Sales teams. The role includes auditing and mapping current content across multiple platforms, designing a unified content architecture, creating governance frameworks for content management, and building a single source of truth for sales teams. The lead will own and evolve LMS and internal knowledge systems, evaluate and implement modern content management tools, build integrations connecting content systems to seller workflows, and design personalized learning paths. They will build and deploy AI-powered sales agents, contribute to GTM agent swarm strategy, design agents for seller support, and use ElevenLabs' voice and agent technology for enablement. The role involves defining "Agentic Enablement," building AI coaching tools, and creating systems for auto-updating content. Coordination across Product Marketing, Company Ops, and RevOps for knowledge management alignment is required. Success metrics include tracking content freshness, usage, findability, time-to-answer, building dashboards for system health, and continuously improving content and agent performance. The role also involves documenting best practices and influencing the evolution of the systems function as Sales Enablement scales.
Freelance Junior Journalist - AI Trainer
As an AI Trainer - Junior Journalist, your work involves training AI models to help them understand and generate human-like text. Tasks include crafting original, clear, and fact-checked responses based on project guidelines, generating prompts that challenge AI, defining comprehensive scoring criteria to evaluate the accuracy of the AI's answers, and following style and quality standards to ensure consistency. The work is project-based, and contributors participate by completing tasks that help shape AI reasoning, logic accuracy, nuance, and clarity in text generation.
Machine Learning Developer (Freelance)
Contributors may design original computational STEM problems that simulate real scientific workflows, create problems requiring Python programming to solve, ensure the problems are computationally intensive and cannot be solved manually within reasonable timeframes, develop problems requiring non-trivial reasoning chains and creative problem-solving approaches, verify solutions using Python with standard libraries such as Numpy, Pandas, Scipy, and scikit-learn, and document problem statements clearly while providing verified correct answers.
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