Data Science Engineer
4 days ago
Dailoqa is seeking a talented Data Science Engineer to lead the development of cloud-based machine learning operations (MLOps) solutions. As a key member of our team, you will design, implement, and deploy cutting-edge MLOps solutions to solve complex business problems.
Job DescriptionThe ideal candidate will have 3-7 years of experience in MLOps, DevOps, or related roles, with strong programming skills in Python and proficiency in cloud platforms (AWS, Azure, or GCP) and infrastructure-as-code tools like Terraform. Experience with MLOps frameworks such as Kubeflow, MLflow, or Airflow is also required.
Responsibilities- Design and implement cloud-based MLOps solutions on platforms such as AWS, Azure, or GCP.
- Develop and maintain CI/CD pipelines for machine learning models using tools like GitLab CI, GitHub Actions, or Circle CI.
- Automate model deployment, monitoring, and retraining processes.
- Containerize models using Docker and deploy them on cloud platforms.
- Set up monitoring tools to track metrics such as response time, error rates, and resource utilization.
- Collaborate with data scientists to review, refactor, and optimize machine learning code.
- Implement version control and governance for models and data.
- Bachelor's degree in Computer Science, Software Engineering, or a related field.
- 3-7 years of experience in MLOps, DevOps, or related roles.
- Strong programming skills in Python, with experience in Go, Ruby, or Bash as a plus.
- Proficiency in cloud platforms (AWS, Azure, or GCP) and infrastructure-as-code tools like Terraform.
- Experience with MLOps frameworks such as Kubeflow, MLflow, or Airflow.
- Solid understanding of Docker, Kubernetes, and container orchestration.
- Familiarity with machine learning frameworks like scikit-learn, TensorFlow, or PyTorch.
$120,000 - $180,000 per year, depending on experience.
About DailoqaDailoqa is a leading Data AI company that empowers businesses to make data-driven decisions. Our team is passionate about leveraging machine learning to drive innovation and growth.
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