Location & work modality:Rubí, Barcelona. #LI-Hybrid
Start: ASAP
Type of Contract: Full Time / Permanent
About Submer The best way to introduce you to Submer is undoubtedly through our values: Sustainable, Unique, Bold, Making Sense, Empathetic and Reliable. If these resonate with you we're sure you will find your place here in no time.
At Submer, we believe that our digital world can be more sustainable, more efficient and more environmentally friendly. Submer is solving the biggest problems of datacenter, supercomputer, hyperscale and edge applications to make that future possible.
Our multinational talented team has a huge passion in reducing IT environmental footprint and expertise in datacenter design and day-to-day operations. We're scaling our team and operations worldwide to meet growing international demand.
What impact you will have As a Machine Learning Solutions Engineer, you will play a pivotal role in designing, implementing, and optimizing AI and ML workflows for our clients. You will work closely with our engineering, product, and customer success teams to deliver scalable and efficient solutions tailored to unique business needs. This is a dynamic, hands-on role that blends technical expertise, problem-solving, and customer interaction.
What you'll do Customer Engagement: Collaborate with customers to understand their AI/ML workflows, compute requirements, and business objectives.Solution Design: Architect tailored GPU-powered solutions that optimize machine learning workloads on our platform.Model Optimization: Assist clients with training, fine-tuning, and deploying machine learning models, ensuring optimal performance on our infrastructure.Infrastructure Integration: Develop and deploy pipelines and tools to integrate client workflows with our platform, including containerization (Docker), orchestration (Kubernetes), and cloud APIs.Performance Tuning: Monitor, troubleshoot, and optimize GPU performance for large-scale ML workloads, including distributed training and inference.Technical Leadership: Provide technical guidance, best practices, and documentation to clients and internal teams.Collaboration: Work with cross-functional teams to refine product features and ensure the platform meets evolving client needs.Innovation: Stay updated on the latest trends in AI/ML, cloud computing, and GPU technologies to continuously improve our offerings.What you'll need Education: Bachelor's degree in Computer Science, Data Science, Engineering, or a related field (or equivalent experience).Experience: 3+ years in a machine learning, data engineering, or solutions engineering role.Strong understanding of machine learning algorithms, training workflows, and model deployment.Experience with popular ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).Familiarity with GPU acceleration and distributed computing (e.g., CUDA, NCCL, Dask, Horovod).Proficiency in programming languages like Python, with exposure to performance optimization techniques.Cloud Expertise: Hands-on experience with cloud platforms (AWS, Azure, GCP) and orchestration tools like Kubernetes.Problem-Solving: Proven ability to diagnose and resolve complex technical issues in real-time.Communication: Excellent written and verbal communication skills, with the ability to convey complex technical concepts to non-technical audiences.What we offer Attractive compensation package reflecting your expertise and experience.Restaurant Pass.Private Health Insurance.Languages classes (English).A healthy work environment with fresh fruits to energise and an on-site gym for active breaks.A great work environment characterised by friendliness, international diversity, flexibility, and a hybrid-friendly approach.You'll be part of a fast-growing scale-up with a mission to make a positive impact, offering an exciting career evolution.Our Inclusive Responsibility Submer is committed to creating a diverse and inclusive environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, or any other protected category under applicable law.
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