MLOps Engineer with English
MLOps Engineer with English
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Job Description
Are you driven by challenges and excited to work with cuttingedge 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 hubsWarsaw Barcelona and Virginia. Now they are expanding their Barcelona team and seeking talented MLOps Engineers to join their missiondriven team.
Join a vibrant Data TechHub 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 largescale 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
Requirements
- 3 years in MLOps with a Masters 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. scikitlearn 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 highload systems and LLM frameworks.
Benefits
- Competitive salary and performancebased bonuses
- Relocation package (if applicable)
- Comprehensive benefits package
- Opportunities for professional development and support for continuing education
- Flexible work hours and vacation policy
Employment Type
Full Time
