Mlops Engineering Manager

Mlops Engineering Manager

Requirements

• Bachelor’s degree in Computer Science, Machine Learning; Master’s degree preferred.
• Minimum of 5 years of experience in a management role, leading machine learning or software engineering teams.
• Minimum of 10 years of hands-on experience in software engineering, with a strong focus on machine learning.
• Deep understanding of machine learning principles, algorithms, and techniques.
• Extensive experience with cloud platforms (e.g., AWS, GCP), including machine learning services (e.g., SageMaker, Vertex AI, Databricks).
• Proven experience with data engineering concepts and tools, including data warehousing, ETL processes, and big data technologies (e.g., Spark).
• Proficiency in Python and experience with machine learning libraries and frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
• Proven understanding of software development standard processes, including version control (Git), CI/CD, and testing.
• Strong experience with containerization and orchestration technologies (e.g., Docker, Kubernetes).
• Experience with data platforms and databases (SQL and NoSQL).

Responsibilities

• Lead and develop a team of software development engineers, fostering a collaborative, innovative environment.
• Drive the design, development, and deployment of end-to-end machine learning systems, from data ingestion and preprocessing to model training, evaluation, and deployment.
• Oversee the building/development and maintenance of our ML platform, ensuring its scalability, reliability, and performance.
• Lead the integration of machine learning solutions with other company services and systems.
• Collaborate with multi-functional teams, including product management, data engineering, and software development, to define project requirements and deliver solutions that meet business needs.
• Stay up-to-date with the latest advancements in machine learning, cloud computing, and related technologies, and drive the adoption of standard methodologies.
• Ensure the quality, security, and compliance of all machine learning solutions.
• Mentor and develop team members, providing technical guidance and fostering their professional growth.
• Manage project timelines, resources, and budgets effectively.
• Contribute to the overall AI/ML strategy of the organization.

Preferred Qualifications

• Excellent communication, collaboration, and leadership skills.
• Strong problem-solving and analytical abilities.
• Ability to thrive in a fast-paced, dynamic environment.
• Proven ability to deliver high-quality machine learning solutions in a production setting.
• Experience with MLOps practices and tools, ideally Kubeflow ecosystem.
• Contributions to open-source machine learning projects.
• Experience with specific machine learning domains (e.g., natural language processing, recommendation systems)