ppbThis position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior AI Research Engineer based in Spain. /b /p pThis role offers the opportunity to build and scale the infrastructure powering next-generation AI solutions for industrial automation. You will work at the intersection of machine learning engineering, MLOps, and research, enabling teams to move advanced AI concepts into production faster. The position focuses on designing reliable systems, optimizing research workflows, and supporting the deployment of intelligent control technologies. You will collaborate with researchers, engineers, and cross-functional teams to transform complex AI experiments into impactful real-world applications. With ownership across the research-to-production lifecycle, you will influence technical direction while solving challenging engineering problems at scale. This is an idóneo opportunity for an experienced engineer passionate about AI, distributed systems, and creating technology with measurable real-world impact. /p h3Accountabilities /h3 ul liOwn and evolve research infrastructure end-to-end, including experiment orchestration, distributed training, model tracking, evaluation workflows, and automated deployment systems. /li liBuild and scale distributed computing solutions for machine learning workloads, including multi-node GPU environments, data pipelines, and cost-efficient infrastructure management across cloud platforms. /li liImprove research and development velocity through performance engineering, including optimizing simulators, training pipelines, profiling bottlenecks, and implementing scalable solutions. /li liAct as a bridge between research and production engineering teams, helping transform AI breakthroughs into reliable production-ready systems. /li liDevelop a deep understanding of internal platforms, tools, and technical capabilities to support effective customer-facing solutions. /li liMaintain clear documentation of research projects, engineering decisions, products, and operational processes.



/li liContribute to medium- and long-term technical decisions that shape research infrastructure and engineering strategy. /li liLead projects from concept to delivery, taking ownership of execution, prioritization, and successful outcomes. /li liMentor team members, share technical knowledge, and support collaborative problem-solving across engineering teams. /li liContinuously improve development practices, tooling, and infrastructure to accelerate AI research and deployment. /li /ul h3Requirements /h3 ul li4+ years of relevant professional experience in software engineering, machine learning engineering, MLOps, or related technical fields. /li liProven experience leading technical projects and owning delivery from initial concept through implementation. /li liPrevious experience working in machine learning research and development environments, ideally connecting research initiatives with production systems. /li liStrong understanding of machine learning and MLOps concepts, including experiment tracking, model lifecycle management, deployment processes, and systems involving non-deterministic components. /li liStrong programming skills in Python and familiarity with lower-level programming languages such as C++ or Rust. /li liSolid engineering foundation combined with scientific understanding in areas such as machine learning, optimization, control systems, or physical sciences. /li liExperience designing scalable infrastructure for AI workloads, distributed computing, or cloud-based environments. /li liStrong problem-solving abilities, curiosity, and willingness to explore unfamiliar technical domains. /li liExcellent organizational, communication, and collaboration skills in a remote and international environment.



/li liAlignment with values centered around transparency, collaboration, ownership, operational excellence, and empathy. /li /ul h3Preferred Skills Experience /h3 ul liExperience with machine learning research, AI systems, or MLOps-focused engineering. /li liFamiliarity with reinforcement learning, simulation environments, or control systems. /li liExperience using distributed computing frameworks such as Ray and managing GPU workloads across multiple nodes. /li liKnowledge of platforms and tools such as PyTorch, SciPy, scikit-learn, NumPy, pandas, MLflow, Docker, Kubernetes, and cloud infrastructure. /li liUnderstanding of industrial systems, including heating, cooling, manufacturing, or data center environments. /li liScientific or technical background that enables effective collaboration with research-focused teams. /li /ul h3Benefits /h3 ul liCompetitive base salary ranging from b£92,065 to £173,648 /b, depending on location tier, experience, qualifications, and other relevant factors. /li liEligibility for meaningful equity participation. /li liFully remote work environment with flexibility across different locations and time zones. /li liMedical, dental, and vision insurance, with benefits varying by region. /li liUnlimited paid time off with a required minimum of 20 days per year. /li liPaid parental leave, depending on regional policies. /li liFlexible stipends supporting workspace setup, personal well-being, and continued professional development. /li liCompany-provided MacBook. /li liTraining programs covering technical development, customer immersion, and professional growth. /li liOpportunity to work in a fast-paced, collaborative environment where your contributions directly influence technical direction. /li liStrong remote culture based on documentation, asynchronous collaboration, regular communication, and virtual team-building activities. /li liSignificant ownership opportunities and the chance to contribute to impactful AI-driven solutions. /li /ul /p #J-18808-Ljbffr

📌 Senior AI Research Engineer (España)
🏢 Jobgether
📍 España