Senior ML Ops Engineer
New
I
Intuition Machines, Inc.Cybersecurity AI/ML
Warsaw, Masovian Voivodeship, Poland. United Kingdom. Czechia. Croatia. Austria. RomaniaContractSenior
Salary not disclosed
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Job Details
- Experience
- Minimum of 3 years of experience in a data role; at least 2 years of professional software development experience in a role other than data engineering.
- Required Skills
- AWSPythonSQLKafkaKubernetesAzureClickhouseNosqlCI/CDMicroservices
Requirements
- Minimum of 3 years of experience in a data role involving designing and building data stores, feature engineering, and building reliable data pipelines that handle high loads.
- At least 2 years of professional software development experience in a role other than data engineering.
- Proficiency in Python and experience working with Kafka infrastructure and distributed data systems.
- Deep understanding of SQL and NoSQL databases (preferably Clickhouse).
- Familiarity with public cloud providers (AWS or Azure).
- Experience with CI/CD and orchestration platforms: Kubernetes, containerization, and microservice design.
- Proven ability to make independent decisions regarding data processing strategy and architecture.
- Thoughtful, self-directed individual who is able to operate effectively in a fast-paced environment.
Responsibilities
- Maintain, extend, and improve existing data/ML workflows, and implement new ones to handle high-velocity data.
- Provide interfaces and systems that enable ML engineers and researchers to build datasets on demand.
- Influence data storage and processing strategies.
- Collaborate with the ML team, as well as frontend and backend teams, to build out our data platform.
- Reduce time-to-deployment for dashboards and ML models.
- Establish best practices and develop pipelines and software that enable ML engineers and researchers to efficiently build and use datasets.
- Work with large datasets under performance constraints comparable to those at the largest companies.
- Iterate quickly, with a focus on shipping early and often, ensuring that new products or features can be deployed to millions of users.
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