MLOps Engineer
Job Summary
Job Description
- Strong knowledge of Python
- Familiarity with Docker
- Basic understanding of machine learning concepts
- Experience with PyTorch
- Familiarity with Kubernetes
- Knowledge of Dagster
- Experience with Kafka
- Understanding of distributed training systems
- Great challenges and opportunities
- Welcoming group of international professionals
- Great corporate culture and internal events
- Cutting-edge hardware and technology
- Work remotely from anywhere in the world
- Access any of our global offices anytime
- 40 paid days off
- Competitive salary
7 skills required
Job Details
We are looking for an experienced MLOps Engineer to join our team. In this role, you will be responsible for improving pipelines for training machine learning models, processing and checking data quality, testing models and ensuring their correctness, and building model monitoring systems. The ideal candidate should be intelligent, contemplative, and composed. They should not rush through tasks, instead diving deeply into the code and being attentive to details.
WHAT YOU’LL BE DOING:
- Design and build ELT pipelines for data processing and analysis.
- Construct MLOps pipelines for automated retraining and validation of models.
- Implement CI/CD pipelines for deploying models and ML services.
- Create services for monitoring ML models in production.
WHAT WE LOOK FOR IN YOU:
- Strong knowledge of Python
- Familiarity with Docker.
- Basic understanding of machine learning concepts and techniques.
WHAT WILL BE A PLUS:
- Experience with PyTorch.
- Familiarity with Kubernetes.
- Knowledge of Dagster.
- Experience with Kafka.
- Understanding of distributed training systems for ML models.
WHY SHOULD YOU JOIN OUR TEAM?
- Great challenges with many opportunities to prove yourself
- A welcoming group of highly qualified international professionals
- Great corporate culture with internal events and surprising commitment to fostering a supportive and empowering environment
- Cutting-edge hardware and technology
- Work remotely from anywhere in the world
- Access any of our global offices anytime
- 40 paid days off
- Competitive salary
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