Top Artificial Intelligence Jobs in Valencia

Own the end-to-end customer-facing conversational agent across chat and voice. Lead roadmap, conversation and interface design, partner discovery and onboarding, prototyping, quality metrics, and agent behavior specification. Work hands-on in Figma, build prototypes with AI coding tools, and iterate from production data with cross-functional GTM and success teams.

Build end-to-end AI-native product features across frontend, backend, and LLM integrations. Design and deploy agent workflows, streaming real-time interactions, memory, and tool integrations. Improve reliability, observability, fallbacks, and reduce latency while collaborating with ML and product teams to ship production-grade, multi-step workflow capabilities.

Build and ship end-to-end AI features: design prompts, tools, memory, and agent workflows; turn model outputs into reliable behavior; debug across model, orchestration, infra, and UX; optimize latency, cost, and reliability; develop evaluation frameworks and collaborate with product and engineering to deliver robust ML-powered features.

Nebius seeks a Senior ML Engineer for AI R&D focusing on applied research in reinforcement learning and agent training, requiring deep expertise in machine learning and software engineering.

Partner with Account Executives to present Arize's GenAI observability platform, lead technical demos and discovery, design and run PoCs, advise on GenAI/LLM best practices, handle technical objections, and build relationships with technical and business stakeholders across prospective customers.

The AI Developer will design, implement, and deploy AI agents and workflows, integrating advanced models and ensuring reliable performance in production environments.

Own product capabilities that improve brand visibility across search engines and LLMs. Evaluate visibility signals (backlinks, mentions, PR, communities), design agentic AI workflows, advise on off-page and technical SEO, analyze review ecosystems and media channels, prototype AI-agent solutions, and drive customer adoption with cross-functional teams.

Lead end-to-end architecture for enterprise data, analytics, and AI in a Microsoft-first environment. Translate business needs into secure, scalable designs, prototype and guide delivery teams, ensure governance, security, and production readiness, and enable enterprise AI (Azure OpenAI, RAG) and BI (Power BI) solutions.

Design and operationalise large-scale GPU AI/HPC datacentre deployments with partners. Advise customers on power distribution, cooling, MEP integration, run PoCs, troubleshoot scaling and performance, deliver technical workshops, and feed product and infrastructure insights back to engineering and business teams.

Build and operate distributed backend services and genomic reasoning engines that combine whole genome bioinformatics with AI. Design scalable data models, retrieval and vector search systems, and deterministic guardrails to ensure scientifically accurate, explainable genomic AI for production use.

Design and build production AI systems and distributed backend services that enable genomic reasoning, retrieval, and data platforms. Integrate genomic annotations and interpretation logic, architect high-performance data models and storage across PostgreSQL, DuckDB, Qdrant, Redis, and Spark. Ensure AI outputs are accurate, explainable, and grounded in genomic evidence while collaborating across engineering and bioinformatics teams.

Develop and optimize large neural-network tabular models in Python. Profile training and inference pipelines, improve memory efficiency, latency, and throughput. Implement performance-critical components in Rust (and optionally C++), ensure numerical stability and reproducibility, collaborate with researchers to productionize capabilities, and maintain tests and documentation.

Ship real open-source integrations and MCP servers to bring SearchApi to agent and automation frameworks. Create PRs, example apps, docs, and integration guides. Stay current with the agent ecosystem, pick high-leverage targets, and work independently to deliver production-ready integrations.

Create short- and long-form AI-generated educational and entertainment content for Instagram, TikTok, and YouTube. Rapidly test content hypotheses, analyze performance, research trends and competitors, and iterate on hooks, storytelling, and editing. Collaborate with the product team and continually experiment with AI image/video generation and editing tools.

Lead and build Maze’s new AI-native Market Research service: define research vision and methodologies, recruit and manage a research team, own delivery quality, partner with Product/Engineering and GTM, and serve as executive research lead on strategic customer engagements.

The Senior ML Engineer will create and improve ML models, collaborate with teams, monitor models in production, and maintain documentation.

Design, build, and deploy production-quality AI/ML solutions (NLP & Computer Vision). Own end-to-end ML lifecycle including data cleaning, model development, MLOps, automated deployment, monitoring, testing, and optimization in cloud environments.

Serve as embedded technical lead to design, build, and demo production-grade agentic AI solutions for slot/casino game production. Deliver prototypes on real game stacks (math engine, backend, client), create transferable agentic harnesses/loops, own model selection, deployment, cost/monitoring, and lead knowledge transfer and client-facing technical engagement.

Remote, asynchronous role evaluating AI-generated Catalan text and audio for accuracy, tone, grammar, and cultural relevance. Provide corrections and constructive feedback via an online platform, ensuring consistency and quality across evaluations. Expect approximately 10 hours of work per week.

Design, prototype, and ship AI-powered features and agent/LLM workflows for analytics and large datasets. Rapidly iterate with user feedback, integrate agentic components with internal tools, and ensure scalable, production-grade solutions while collaborating across the team.

Build production AI-native systems for BJAK's neobank: AI agents, RAG/LLM apps, tool-calling, automations and copilots for onboarding, KYC, support, risk, CRM and operations while addressing accuracy, hallucination, latency, cost, security and compliance.

Adapt and review scripts for AI dubbing, ensure natural and accurate German localization, review AI-generated dubbing outputs for quality, collaborate with teams to improve language and creative outcomes, and manage multiple projects to deadlines.

Remote AI/ML Architect to assess current AI/ML landscape, document requirements, and propose SDLC, governance, and deployment approaches. Provide recommendations to architecture and ICT management. Onboarding in the Netherlands (first week). Candidates must be based in Europe with a valid work permit.

Design and document the current AI/ML landscape, capture requirements, propose SDLC approaches and tooling, and advise architecture and ICT management on AI/ML solution design, governance, and deployment. Remote role with first-week onboarding in the Netherlands.

Lead and build Axelera's AI Infrastructure Systems division to deliver datacenter-class hardware from accelerator cards and OAM/UBB modules to 1U/2U racks. Own architecture, schematics, PCB/layout review, power/thermal/mechanical design, BMC/firmware, bring-up, validation, qualification, NPI, and ramp with CMs/ODMs. Align roadmaps with silicon, SDK, and product teams, engage customers and partners, set engineering processes, manage budget and vendor relationships, and mitigate technical risks through hands-on leadership.