Machine Learning Engineer

GCP Requirements:

• Vertex AI & Kubeflow Pipelines: Experience working with Vertex AI pipelines or Kubeflow pipelines, driving the orchestration of machine learning workflows in a cloud-native environment.

• BigQuery: Strong familiarity with BigQuery for large-scale data querying, capable of writing optimized SQL queries.

• Cloud Composer / Airflow: Proficiency in managing data workflows with Cloud Composer or Apache Airflow, ensuring smooth orchestration and scheduling of tasks.

• IAM & Service Accounts: Deep understanding of Identity and Access Management (IAM) and working with service accounts to manage permissions securely.

• Data Catalog: Familiar with Google Cloud Data Catalog, enabling data governance, metadata management, and discovery across various datasets.

• Infrastructure as Code (IaC): Practical understanding of Infrastructure as Code principles, ensuring the automation and scalability of cloud resources.

• Bonus Knowledge: Familiarity with Dataflow and Kubernetes (K8s) for streamlining data processing and container orchestration.

Cloud-Agnostic Skills:

• Python: Expertise in Python programming with a solid foundation in Object-Oriented Programming (OOP) and coding best practices. Experience with tools like flake8, mypy, black, SonarQube, and pre-commit for code quality and formatting.

• Testing: Advanced knowledge of unit and end-to-end testing, with experience using frameworks such as Pytest, fixtures, and unittest to ensure reliable and maintainable code.

• Unix: Comfortable with Unix-based systems, with practical experience in installing software within Docker containers and working with shell scripting.

• Git: Proficient in using Git, including creating Pull Requests (PRs), resolving merge conflicts, and managing version control. Ability to set up CI/CD pipelines using GitHub Actions following industry best practices.

• Docker: Strong understanding of containerization with Docker, enabling smooth deployment and scaling of applications.

• DBT: Expertise in Data Build Tool (DBT), preferably in a Google Cloud environment, for managing and transforming data pipelines efficiently.

• SQL & Data Modeling: Profound knowledge of SQL and data modeling techniques, as well as system design principles, to ensure high-quality, scalable data architecture.

Soft Skills:

• Problem-Solving Mindset: A proactive approach to tackling challenges, with a strong ability to learn new technologies quickly. Resourcefulness and a solution-oriented mindset, such as knowing how to effectively research and resolve unfamiliar issues.

• Communication: Excellent communication skills, with the ability to collaborate effectively with both stakeholders and technical teams, bridging the gap between business needs and technical requirements.

• Code Review & Feedback: A strong advocate for code quality, including conducting thorough code reviews and embracing constructive feedback to continuously improve the development process.

Additional Experience (Merit):

• Previous experience working with high-availability APIs, machine learning-based recommendation systems, and personalization engines is a plus. This is particularly relevant for teams focusing on customer-facing recommendation systems.

This role offers an exciting opportunity to contribute to cutting-edge projects while working in a collaborative environment, driving innovative solutions with the latest cloud technologies.

About Rasulson Consulting

Rasulson Consulting is a specialized staffing and recruitment firm focused on the IT sector. We collaborate with leading tech companies and innovative startups to provide exciting career opportunities for individuals passionate about digital development. With our deep technical expertise and extensive network, we efficiently match the right talents with the right assignments. At Rasulson Consulting, you'll receive personalized guidance, regular feedback, and the chance to take the next step in your IT career.