Machine Learning Engineer

Melio is seeking a passionate Machine Learning Engineer to join our expanding team:

  • Level: Junior or Intermediate
  • Position: Full time
  • Salary: Based on technical experience
  • Location: South Africa (Remote)

As a fast-paced start-up, our day-to-day is never the same. We look for candidates who love to take up new challenges and have the flexibility to go above-and-beyond the call of duty.

That being said, this specific role is for a team member to work in the Machine Learning AI team as a Machine Learning Engineer.

Job Description

The candidate will be working with clients on projects focused on delivering reliable data-powered software applications to production. The primary focus of the role includes designing and implementing data pipelines, building models (machine learning or not), and deploying models.

Melio believes in nurturing cross-functional capabilities in our team, so you will need to work closely with other technical roles, such as BI specialists, data scientists, DevOps engineers and other data and machine learning engineers either to observe or to assist.

This is a technical role, but due to the consulting nature of many of our projects, the candidate needs to be able to communicate effectively with both business and technical stakeholders.

The list below is for both machine learning engineer and data engineer, but we are not expecting you to perform as both an ML engineer and a data engineer. The idea is you should be sufficiently comfortable with either role to be aware and able to communicate and learn from your colleagues.

Primary Requirements

  • Fluent with the following languages: Python, Spark, PySpark, SQL.
  • Strong analytical skills and passion for solving data problems.
  • Strong communications skills and comfortable presenting your own thoughts to technical and business stakeholders.
  • Familiar with building training and inference pipelines for ML projects.
  • Familiar with fundamental machine learning theory and building, tuning, selecting models.
  • Familiar with MLOps principals.
  • Some experience with at least one Cloud provider.
  • Some experience working with test automation and tools.
  • Implement and test data engineering and machine learning software.
  • Build and test data engineering and machine learning pipelines for data analytics or machine learning solutions.
  • Collaborate and share technical knowledge with team members and co-workers.
  • Follow all best practices and procedures as established by the client or industry.
  • Document designed solutions and implemented tools.
  • Brainstorm new solutions to improve data and ML software development and deployment.
  • Basic understanding of the cloud-native ecosystem and desire to learn and grow in this environment.

Secondary Responsibilities

  • Assist with setting up CI (Continuous Integration) and CD (Continuous Delivery) tools with the team.
  • Monitor data/model metrics, and develop ways to improve application development and deployment.
  • Maintain day-to-day management and administration of projects.

Qualification & Experience

Minimum Requirements

  • Bachelor’s degree in Computer Science, Engineering, Software Engineering, Applied Mathematics, Statistics, or related field.
  • 2+ years experience working with data science and data engineering. Previous experience with software development (e.g. Python, Java, Go).

Desired Skills

  • Contribute and/or passionate about open source projects.
  • Start up/side project/product experience.
  • Masters/PhD in Data Science, Machine Learning or AI.
  • AWS certifications (or any other cloud).
  • Interested in learning more about Cloud Native Computing Foundation technologies.

Personal Attributes

  • Up-to-date on latest industry trends; able to articulate trends clearly and confidently.
  • Good interpersonal skills and communication with all levels of management.
  • Able to multitask, prioritize, and manage time efficiently.
  • Curious and eager to learn about new technologies.
  • Strong in critical thinking and problem-solving.