Machine Learning Operations (ML/Ops) Engineer - Team Lead

Machine Learning Operations (ML/Ops) Engineer - Team Lead

Location / Work Setup: Remote

About Us:

We are a dynamic and innovative team currently engaged in an exciting Request for Quote (RFQ) process for a client based in Hong Kong. We are on the lookout for a skilled Machine Learning Operations Engineer, particularly someone experienced in deploying Machine Learning models into pipelines. This is a fantastic opportunity to be part of a high-impact project where your contributions will shape the future capabilities of our client's ML infrastructure.

Key Responsibilities:

• Lead a team of ML/Ops engineers in deploying and managing Machine Learning models.
• Build and enhance capabilities to seamlessly integrate ML models into existing pipelines.
• Collaborate with cross-functional teams to understand project requirements and ensure successful deployment.
• Provide ongoing support to accommodate surges in requirements, focusing on scalability and efficiency.
• Utilize Python for scripting and automation tasks.
• Work with Cloud platforms, particularly Azure and GCP to optimize machine learning workflows.

Requirements:

• For Team Lead Position:
  • At least 3 years of experience in ML/Ops or a related field.
  • Proven leadership skills with the ability to guide and inspire a team.
  • Excellent communication skills to effectively liaise with clients and internal teams.
• For ML/Ops Engineer Position:
  • Strong experience in deploying Machine Learning models.
  • Proficiency in Python for scripting and automation.
  • Hands-on experience with Cloud platforms, particularly Azure and GCP.
  • Prior experience in addressing scalability and pricing concerns in ML operations.

How to Apply:

If you are a passionate ML/Ops professional ready to take on a leadership role or contribute your expertise to a cutting-edge project, we want to hear from you. Please submit your resume, highlighting your relevant experience, and a cover letter detailing your approach to scalability and pricing in ML operations.

Note: This is a unique opportunity to make a significant impact on a client's ML capabilities, and we are excited to welcome individuals who share our enthusiasm for innovation and excellence.