Cloud Machine Learning Engineer

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Cloud Machine Learning Engineer in Spain.

The Cloud Machine Learning Engineer will design, build, and deploy scalable machine learning solutions leveraging cloud technologies. This role bridges advanced ML frameworks with cloud platforms to deliver performant, secure, and user-friendly APIs and developer experiences. You will collaborate with cross-functional teams to ensure models are optimized, integrated, and documented effectively for a global user base. The position requires hands‑on experience in deep learning frameworks, cloud infrastructure, and MLOps practices, with a focus on efficiency, reproducibility, and developer usability.

The ideal candidate thrives in a distributed, innovation-driven environment, enjoys sharing knowledge with the community, and contributes to solutions that impact millions of users worldwide. You will also have the opportunity to influence best practices, technical standards, and cloud ML architecture at scale.

• Integrate machine learning models with cloud platforms and managed SaaS solutions to deliver robust production systems.
• Ensure deployed ML models meet performance, reliability, and scalability requirements.
• Design, develop, and maintain secure and user-friendly developer APIs and interfaces.
• Build and optimize MLOps pipelines, including containerization with Docker and orchestration with Kubernetes where applicable.
• Write technical documentation, tutorials, and examples to support internal teams and external users.
• Collaborate with cross-functional teams, including data scientists, engineers, and product managers, to align development efforts with strategic goals.
• Advocate and share technical solutions and achievements with internal stakeholders and the broader developer community.

• Strong experience with ML frameworks, preferably PyTorch, and ML libraries such as Transformers, Diffusers, Accelerate, and Datasets.
• Proficiency with cloud platforms such as AWS, Azure, or GCP, including services like Sage Maker, EC2, S3, or equivalents.
• Experience building MLOps pipelines for model deployment, monitoring, and containerization.
• Familiarity with programming and scripting languages such as Python; knowledge of Typescript, Rust, or Mongo
  
  DB is a plus.
• Ability to write clear, reproducible documentation and examples to support development and adoption.
• Experience across the full ML product lifecycle, from research and prototyping to production deployment and monitoring.
• Strong problem-solving, collaboration, and communication skills in a distributed team environment.

• Experience with front-end frameworks or styling libraries such as Svelte and Tailwind
  
  CSS.
• Exposure to open-source ML communities and contributions.
• Understanding of XLA, hardware accelerators, or distributed training techniques.

• Competitive salary and equity package.
• Flexible work hours and fully remote work options with potential visits to office locations.
• Comprehensive health, dental, and vision insurance for employees and dependents.
• Parental leave and flexible paid time off policies.
• Professional development opportunities, including training, conferences, and workshops.
• Ownership and impact: equity participation to align with company success.
• Inclusive and supportive work culture with emphasis on learning, growth, and collaboration.

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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