MLOps Engineer (P806)
About Us:
As a Senior MLOps Engineer at Kenility, you will become part of a collaborative team of developers, engineers, and designers focused on delivering top-quality software solutions to the market.
Technical Requirements:
- Bachelor’s degree in Computer Science, Software Engineering, or a related field.
- Extensive experience in DevOps and MLOps, particularly using Terraform and CI/CD practices.
- In-depth knowledge of AWS networking, security architecture, and containerization technologies.
- Proficient in using Atlassian tools including Jira, Confluence, and Bitbucket pipelines.
- Skilled in programming with languages such as Python, Go, Java, or Scala.
- Solid understanding of big data technologies like Hadoop and Spark.
- Hands-on experience with machine learning frameworks and libraries such as TensorFlow, XGBoost, and scikit-learn, as well as MLOps tools.
- Holds certifications such as AWS Certified Cloud Practitioner, AWS Certified Machine Learning Engineer, or AWS Certified DevOps Engineer (strongly preferred).
- Minimum Upper Intermediate English (B2) or Proficient (C1).
Tasks and Responsibilities:
- Work closely with data scientists, ML engineers, and data engineers to architect scalable and reliable ML pipelines and real-time inference systems.
- Automate the complete machine learning lifecycle, from data ingestion through training, evaluation, deployment, and monitoring.
- Design and manage CI/CD pipelines tailored for ML model integration and deployment.
- Monitor model performance post-deployment, ensuring alignment with business goals and performance criteria.
- Support the configuration and optimization of monitoring systems for deployed models.
- Identify and resolve issues affecting ML model deployment and performance.
- Continuously explore new tools and advancements relevant to MLOps and ML engineering.
Soft Skills:
- Responsibility
- Proactivity
- Flexibility
- Great communication skills
