Machine Learning Engineer (MLOps)
Role details
Job location
Tech stack
Job description
- Design, implement, and maintain end-to-end pipelines for ML model deployment, monitoring, and lifecycle management.
- Develop automated workflows for CI/CD in ML systems to ensure rapid and reliable deployments.
- Implement robust monitoring and alerting systems for production ML models to ensure performance and reliability.
- Develop and improve Python scripts responsible for algorithmic decision making, generating alarms, data quality and model quality dashboards.
- Troubleshoot issues in real-time and ensure high availability of deployed systems.
- Collaborate with the Machine Learning team to manage model retraining and updating processes.
- Write, review and maintain high-quality Python code for MLOps tooling and automation., * Top location at the heart of Barcelona in a penthouse office with a rooftop terrace, barbeque, and a fully stocked fridge.
- Work from home: 2 days/week
- Private Health Insurance
- Access to LinkedIn Learning
- Meal vouchers - Tickets Restaurant monthly allowance.
- Monthly gym allowance: Choose between DiR Gym and Wellhub
- Monthly TGIF events.
- Regular team-building events.
- Fun and friendly work environment with talented marketers and engineers from over 40+ countries
- And more!
Requirements
We are seeking a highly skilled and motivated Senior Machine Learning Engineer to join our MLOps team. The ideal candidate will have a strong background in Python coding, and knowledge of the ML lifecycle and MLOps industry best practices. This role will be part of MLOps, a horizontal sub-team within the ML team, that focuses on making the end-to-end ML lifecycle scalable, reliable and efficient., * 5+ years of experience in the ML Engineering field.
- Proficiency in Python and familiarity with data related processing libraries (e.g., Pandas, NumPy).
- Good understanding of CI/CD pipelines and DevOps practices
- Strong Interest in machine learning topics
- Experience in Linux environments
- Fluency in English is mandatory
- Possesses good communication skills both verbal and written
- Strong problem-solving and analytical skills.
Please note that we do not provide visa sponsorship. Candidates without a legal permit to work won't be considered.
Extra points for :-)
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Master's degree in Computer Science or related fields
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Familiarity with AWS services such as EMR, EC2, Athena, S3
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Hands-on experience with ML workflow orchestration tools (e.g., Airflow, MLflow).
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Experience with cloud platforms (preferable AWS) and containerization technologies (Docker, Kubernetes).
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Knowledge in infrastructure tools (IaC) like Terraform.
Benefits & conditions
- Great compensation package.
