MLOps Engineer with English (Full Remote)

Are you driven by challenges and excited to work with cutting-edge technologies?

Are you ready to tackle the challenge of managing the full model lifecycle in a dynamic production environment?

Are you passionate about taking machine learning models from prototype to production?

Our client, an innovative tech startup, operating across three dynamic hubs—Warsaw, Barcelona, and Virginia. Expanding their Barcelona team, is seeking talented MLOps Engineers to join their mission-driven team. Although you won't need to relocate to Barcelona, we'll have offline 1 week workshops (on-site) every quarter.

Join a vibrant Data Tech-Hub where a passionate team of Machine Learning, Data Analysts, and Data/ML Engineers is ready to innovate and inspire!

Key Languages

Full Professional level of English

Main Responsibilities

• Provision and manage AWS ML resources and infrastructure
• Develop MLOps pipelines and CI/CD pipelines on the AWS platform
• Deploy and manage ML models in production environments
• Support large-scale ML challenges using distributed training frameworks
• Use and create Terraform libraries for infrastructure setup
• Oversee infrastructure from development to production, with security monitoring and administration
  
  

Core Skills/experience

• 3+ years in MLOps, with a Master’s or Ph.D. in a relevant field (or equivalent experience)
• Skilled in designing and implementing MLOps pipelines across the full ML lifecycle on AWS
• Proficiency in MLOps frameworks (e.g., Kubeflow, MLFlow, SageMaker) and cloud platform architecture
• Strong Python skills, Linux knowledge, and familiarity with ML libraries (e.g., sci-kit-learn, Keras, PyTorch, TensorFlow)
• Expertise in DevOps, CI/CD, data security, and AWS CloudFormation or Terraform
• Understanding of core CS concepts, including data structures and algorithms
• Ability to monitor new MLOps tools and solutions, and collaborate effectively
• Great plus to have!! ML certification, experience with GCP, Azure, Docker, Kubernetes, Snowflake, BigQuery, Databricks, Vector Databases, high-load systems, and LLM frameworks.
  
  

What's On Offer

• Competitive salary and performance-based bonuses
• Relocation package (if applicable)
• Comprehensive benefits package
• Opportunities for professional development and support for continuing education
• Flexible work hours and vacation policy
  
  

Our recruitment process?:

Step 1: Interview with our Recruiter to get to know you

Step 2: Interview with our client's Head of People

Step 3: Technical interview

Step 4: Interview with Hiring Manager