About this role
Our client is seeking a Senior MLOps / Machine Learning Engineer to design, build, and scale their next-generation machine learning infrastructure. In this pivotal role, you will bridge the gap between Data Science and Core Engineering, ensuring that predictive models transition smoothly from experimental notebooks to high-throughput, production-grade systems. This position is focused on managing real-world scale, rather than simply setting up low-traffic inference endpoints.
Key Responsibilities:
- Design and implement scalable machine learning infrastructure.
- Collaborate with Data Scientists to transition models into production.
- Optimize and maintain high-throughput systems for real-time data processing.
- Monitor and troubleshoot production ML systems to ensure reliability and performance.
- Develop best practices for model deployment and monitoring.
Required Skills & Qualifications:
- Strong experience with MLOps practices and tools.
- Proficiency in programming languages such as Python and frameworks like TensorFlow or PyTorch.
- Familiarity with cloud platforms (AWS, GCP, Azure) for deploying machine learning solutions.
- Experience with containerization technologies (Docker, Kubernetes).
- Solid understanding of data engineering principles and data pipelines.
Experience:
- 5-8 years of relevant experience in machine learning engineering or MLOps.
What we offer:
- Opportunity to work on cutting-edge technology in a dynamic environment.
- Collaborative culture with a focus on innovation and continuous learning.
- Access to professional development resources and training.
This role is managed by AI-First Talent on behalf of our client. Your application is reviewed directly by our talent team.