Lead Machine Learning Engineer

Placements24; Durban; Híbrido; ZAR 2 501 000 - 3 835 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Health benefits

Remote work stipend

Professional development budget

Generous paid time off

Access to advanced computing resources

Resumo da oferta

Placements24 is seeking a dynamic Lead Machine Learning Engineer to spearhead ML initiatives. This remote-first role leads a team of engineers, shapes model architecture, and drives deployment and maintenance of scalable ML systems.

You will collaborate with data scientists, software engineers, and product managers, mentor junior engineers, and advance MLOps practices. A strong background in Python, TensorFlow/PyTorch, and cloud platforms is required for success.

Qualificações

• Advanced degree in CS, ML or related field.
• 5+ years in ML engineering with production deployments.
• Proficient in Python and ML libraries (TensorFlow, PyTorch, scikit-learn).
• Experience with MLOps and tools (Kubeflow, MLflow, Docker, Kubernetes).
• Experience with AWS/Azure/GCP.
• Strong software engineering practices (CI/CD, testing, version control).
• Excellent leadership and communication skills.
• Comfort working in a fully remote, collaborative team.

Responsabilidades

• Lead design and deployment of ML models and pipelines.
• Mentor ML engineers and guide technical growth.
• Oversee production ML systems monitoring and optimization.
• Collaborate with data scientists, engineers, and product managers.
• Develop robust MLOps practices for lifecycle management.
• Identify business problems to solve with ML.
• Architect scalable ML infrastructure.
• Ensure quality, reliability, performance of ML solutions.
• Stay current with ML and MLOps advancements.
• Contribute to code reviews and design discussions.

Conhecimentos

Python

TensorFlow

PyTorch

Scikit-learn

MLOps

Kubeflow

MLflow

Docker

Kubernetes

AWS

Azure

GCP

CI/CD

Leadership

Communication

Formação académica

Master's degree in CS/ML

PhD in CS/ML

Ferramentas

Kubeflow

MLflow

Docker

Kubernetes

Descrição da oferta de emprego

About the Role

Our client is looking for a dynamic and experienced Lead Machine Learning Engineer to spearhead their machine learning initiatives. This is a fully remote position, offering you the flexibility to work from anywhere while contributing to groundbreaking AI projects. You will lead a team of talented engineers, driving the development, deployment, and maintenance of scalable machine learning systems. This role demands a blend of strong technical expertise, leadership capabilities, and a passion for innovation. As a remote-first organization, we are committed to providing a supportive and collaborative virtual environment where you can excel. Your expertise will be crucial in shaping the future of our client's AI-driven products and services. We empower our remote team members with the tools and autonomy needed to succeed in this challenging and rewarding field.

Key Responsibilities

• Lead the design, development, and implementation of machine learning models and pipelines.
• Mentor and guide a team of machine learning engineers, fostering their technical growth.
• Oversee the deployment, monitoring, and optimization of machine learning systems in production.
• Collaborate with data scientists, software engineers, and product managers to define ML requirements.
• Develop and maintain robust MLOps practices for efficient model lifecycle management.
• Identify opportunities to leverage machine learning to solve complex business problems.
• Architect scalable and resilient ML infrastructure.
• Ensure the quality, reliability, and performance of ML solutions.
• Stay current with the latest advancements in machine learning and MLOps.
• Contribute to code reviews and technical design discussions.

Requirements

• Master's or Ph.D. in Computer Science, Machine Learning, or a related quantitative field.
• 5+ years of experience in machine learning engineering, with a proven track record of building and deploying ML systems.
• Strong programming skills in Python and proficiency with ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Expertise in MLOps principles and tools (e.g., Kubeflow, MLflow, Docker, Kubernetes).
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Solid understanding of software engineering best practices, including CI/CD, testing, and version control.
• Excellent leadership, communication, and interpersonal skills.
• Ability to work effectively in a fully remote, collaborative team environment.
• Experience with data engineering and large-scale data processing is a plus.
• Demonstrated ability to mentor junior engineers and lead technical projects.

Benefits

• Highly competitive salary and bonus structure.
• Comprehensive health and wellness benefits.
• Generous paid time off.
• Professional development budget and opportunities for continued learning.
• Remote work stipend for home office setup.
• Access to advanced computing resources.
• Collaborative and innovative remote work culture.
• Opportunities to work on challenging and impactful AI projects.