Data/MLOps Engineer - Blue White team

InterVenture

3.6

Beograd, Novi Sad, Niš | Hibrid

24.07.2024.

NoSQL Python AWS Jenkins Azure Bash Cloud intermediate

Our partner - Blue White is a Tel Aviv-based world leader in autonomous technologies and unmanned systems. Their solutions aim to optimize operations and productivity in various domains like agriculture, security, and smart mobility and to help their customers adopt new autonomous technologies to improve the efficiency and effectiveness of the existing products & services.

The team of 100+ professionals comprises autonomous operation experts, system engineers, robotics experts, and optimization & AI algorithms developers.

BWR is building a revolutionary RaaS (Robot-as-a-Service) platform and on that note, together we are looking for a:

Data/MLOps Engineer

You will be responsible for building and maintaining robust data pipelines, deploying and managing machine learning models in production, and ensuring the reliability and scalability of our Data and ML infrastructure.

Your responsibilities:

Design, build, and maintain scalable data pipelines to support machine learning workflows.
Implement and manage MLOps practices to streamline model development, deployment, and monitoring.
Collaborate with data and ML engineers to integrate machine learning models into production systems.
Develop and maintain CI/CD pipelines for model training, validation, and deployment.
Monitor and troubleshoot data pipelines and ML models in production to ensure high availability and performance.
Optimize data storage solutions for efficient data access and processing.
Implement data governance and security best practices.
Stay up-to-date with the latest advancements in data engineering, MLOps, and cloud technologies.

Requirements:

2+ years of experience in DataOps, MLOps, or related fields.
University degree in Computer Science or Software Engineering.
Proficiency in any programming or scripting language such as Bash, and Python.
Experience with relational and NoSQL databases.
Experience with data lakes and warehouses managing large-scale data storage and structured data solutions (ClickHouse, Apache Iceberg).
Experience with cloud platforms such as AWS, Google Cloud, or Azure.
Experience with containerization and orchestration tools like Docker and Kubernetes.
Strong understanding of CI/CD practices and tools such as CodeBuild, ArgoCD, Jenkins, GitHub Actions, etc.
Strong proficiency in infrastructure orchestration using Terraform
Experience with monitoring and logging tools like Prometheus, Grafana, or ELK Stack.
Experience with networking protocols and technologies
Excellent problem-solving skills and attention to detail.
Strong communication and collaboration skills.

Preferred skills:

Experience with data processing and integration frameworks such as Apache Spark, Kafka, Airbyte, and Airflow
Experience with machine learning frameworks and libraries such as Pandas, PyTorch, TensorFlow
Experience with MLOps platforms such as ClearML and MLFlow
Experience with ML-dedicated data management and labeling platforms such as Voxel51, Rekognition, Roboflow
Knowledge of data governance and compliance standards (e.g., GDPR, HIPAA).
Experience with feature stores and model registries.
Familiarity with data visualization tools and libraries.