Top Machine Learning Jobs in Seville

Lead and mentor a data science team developing machine learning systems for threat detection and agentic AI. Set ML technical strategy, standards, roadmaps, and deployment practices; guide projects from research through production; collaborate with security, engineering, and product teams; develop advanced malware and behavioral threat models; communicate insights; and contribute to research, publications, patents, and hands-on technical work.

Design and build production-grade agentic AI and ML solutions, including LLM and RAG systems, end-to-end data architectures, multi-agent workflows, guardrails, monitoring, and automated actions. Collaborate with engineering, project, and client teams to prioritize use cases, explain technical decisions, and deliver prototypes through production. Contribute to real-time data pipelines, AI evaluation, governance, and team knowledge sharing.

Develop and deploy AI-powered 3D graphics solutions for desktop, web, VR, and AR applications using the Evergine engine. Build computer vision and spatial computing models, including NeRF, Gaussian Splatting, point-cloud processing, SAMv2, and GroundingDINO or FlorenceV2. Design scalable algorithms, integrate machine learning frameworks, and collaborate with research and engineering teams in an Agile environment.

The AI Engineer will build data pipelines and improve ML systems for reliability in production. Responsibilities include schema design, data infrastructure, and model evaluation, ensuring high-quality outputs and integration with product workflows.

Own the Mapping & Content product domain end to end, including strategy, prioritization, economics, and outcomes. Lead efforts to match hotel rooms and content across suppliers, languages, and formats with high accuracy and coverage. Partner closely with engineering and data science teams on entity resolution, search, matching, catalog, identity, recommendation, and content-quality problems. Identify high-value failures, make trade-offs between precision and coverage, and help build Nuitee’s product organization in a fast-moving environment.

Lead research on interactive avatar models and real-time generative AI video agents. Set research direction, advance multimodal perception and reaction generation, post-train diffusion models, build evaluation frameworks, define datasets, and guide research-to-production efforts. Mentor researchers and influence technical decisions across research, data, and engineering teams.

Own the global B2B content strategy for enterprise audiences, creating content across websites, advertising, whitepapers, case studies, thought leadership, social, video, and sales enablement. Build AI-assisted content production systems with prompt libraries, source-of-truth repositories, agentic workflows, and human review controls. Partner with Product, Sales, and regional Marketing teams to develop enterprise messaging and improve content quality using performance data.

Design, develop, train, deploy, optimize, and monitor production AI and machine learning solutions. Responsibilities include data cleaning and transformation, scalable ML pipeline development, MLOps automation, model testing, infrastructure deployment, and applied work in NLP and computer vision. The role involves end-to-end software product development, cloud platforms such as Azure, agile collaboration, and delivering customized AI solutions for clients.

Develop machine learning and analytics solutions using large-scale datasets. Responsibilities include feature engineering, predictive modeling, workflow optimization, customer implementations, production deployments, stakeholder collaboration, technical training, and resolving data-related challenges. The role requires Python, PySpark, machine learning pipelines, MLflow or Airflow, statistical modeling, and strong communication skills, with preferred experience in fraud detection, risk analytics, compliance, cloud environments, and model monitoring.

Analyze production drive-thru voice AI data, build SQL reports and dashboards, monitor KPIs, identify conversation error patterns, and improve NLU models, conversation flows, and LLM behavior through machine learning and rule-based techniques.

Build the Ops AI Platform from the ground up, developing reliable AI agents, agent tooling, internal tools integrations, evaluation systems, safety controls, and human-in-the-loop workflows. Scale automation from dozens to tens of thousands of daily tasks while influencing architecture, code quality, product direction, engineering culture, mentoring, and hiring.

Build core components of a diagnostic and personalization platform: backend data pipelines, frontends, services for genomic data ingestion, ML model integration, APIs, and cloud infrastructure. Collaborate with product and ML teams, iterate on prototypes and MVPs, and make architectural decisions supporting scalability and reliability.

Owns full-cycle recruiting for commercial, operational, and technical roles across global markets. Responsibilities include sourcing passive candidates, building pipelines for hard-to-fill positions, advising hiring leaders, coordinating interviews and offers, maintaining accurate Greenhouse data, and improving hiring processes through systems thinking, data, AI, and automation.

Build BLP’s core software across infrastructure, backend, machine learning, and product extension platforms. Responsibilities include operating secure and observable cloud infrastructure, developing performant distributed systems, applying AI to business problems, and enabling customer process automation. The role emphasizes formal reasoning, correctness by construction, maintainable systems, type systems, and functional programming. Work is available onsite in Zurich or remotely within Europe.

Own the Vault product roadmap and lifecycle for a sports media asset platform. Lead discovery with customers, define solutions for content ingest, storage, integrations, AI enrichment, metadata, search, rights, and asset monetization. Partner closely with engineering, sales, and customer success, attend customer events, and prioritize product bets that help sports organizations maximize the value of extensive media archives.

Corti is seeking passionate individuals to join their talent community, shaping the future of healthcare through AI technologies. Opportunities include roles in AI technology, machine learning, and software development, focusing on reducing errors and improving patient outcomes.

Build reproducible bioinformatics workflows with Nextflow, develop cloud and HPC data infrastructures, and deploy scalable pipelines for genomics and other scientific datasets. Engage customers to define requirements, deliver projects, provide training, document solutions, and communicate progress. The role also collaborates with internal teams and applies expertise in programming, omics analysis, cloud architectures, and production bioinformatics software.

Lead data strategy, architecture, governance, quality, compliance, and technology adoption. Translate stakeholder needs into scalable data initiatives, support advanced analytics and AI/ML, promote data literacy, and guide cross-functional teams toward data-driven decision-making.

Build and maintain Ergodic AI’s AI platform across back-end and front-end systems. The role involves developing with Python web frameworks and JavaScript/TypeScript, integrating with client technology stacks and workflows, applying AI, ML, and LLM concepts, and contributing to DevOps, cloud deployment, testing, and infrastructure practices. As an early-stage hire, the engineer will help shape the product and solve complex data and AI challenges.

Develop AI-augmented blockchain risk and threat intelligence systems, including autonomous monitoring and investigation workflows. Lead forensic investigations into crypto theft, fraud, and market manipulation. Research post-quantum cryptography and quantum threats to blockchain security, evaluate migration paths, and collaborate with internal teams, external stakeholders, and academic institutions to deploy emerging security tools.

Supports Account Executives throughout the sales cycle by leading technical discovery, solution design, demonstrations, workshops, proofs of concept, evaluations, and technical validation. Translates engineering, simulation, HPC, AI, and infrastructure requirements into Rescale recommendations, documents opportunities in Salesforce, resolves technical risks, supports negotiations, and ensures effective post-sale handoffs across Northern Europe.

Lead Jampp’s transition to deep learning and embedding-based architectures for large-scale, latency-sensitive programmatic advertising. Design, deploy, and optimize neural network models for bidding, ranking, prediction, and campaign optimization. Establish modeling and production standards, guide architecture and infrastructure decisions, mentor data scientists, and collaborate with engineering teams to build scalable training, serving, and feedback systems.

Review and annotate images by identifying people, actions, and predefined categories. Follow detailed annotation guidelines, maintain accuracy and consistency, review completed work, and help create high-quality datasets for AI models. The role requires strong attention to detail, independent work, reliability, and EU citizenship with residence in the European Union.

Design, develop, evaluate, and deploy deep learning and embedding-based models for real-time advertising prediction, bidding, and optimization. Work with massive, high-cardinality datasets, machine learning pipelines, feature infrastructure, and production model monitoring. Collaborate with data scientists, ML engineers, software engineers, and data engineers to translate experiments into scalable solutions and measure their impact on campaigns and business outcomes.

Lead the Agentic Discovery product chapter, initially owning business tooling, dashboards, transparency, and controls for AI-powered commerce experiences. Define strategy, align ML, engineering, design, and go-to-market teams, scale experimentation, launch reliable LLM-powered experiences, and establish metrics tied to usage, conversion, revenue, and engagement. The role will expand to chapter-wide leadership across on-site, offsite, and integrated agentic discovery surfaces.