MLOps Engineer with English
hace 1 semana
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, specializes in accelerating growth for mobile app businesses globally. With a client base of leading app developers and publishers worldwide, they operate across three dynamic hubs—Warsaw, Barcelona, and Virginia. Now, they are expanding their Barcelona team and seeking talented MLOps Engineers to join their mission-driven team.
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
Tasks- 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
- 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.
- 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
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