About this role
Our client is seeking a Senior MLOps / Machine Learning Engineer with 5-8 years of experience to design, build, and scale their next-generation machine learning infrastructure. In this role, you will bridge the gap between Data Science and Core Engineering, ensuring that predictive models transition from experimental notebooks to high-throughput, production-grade systems seamlessly. This position is focused on real-world scale applications rather than low-traffic inference endpoints.
Key Responsibilities:
- Design and implement scalable machine learning infrastructure.
- Collaborate with data scientists to optimize and deploy predictive models.
- Ensure smooth transition of models from development to production environments.
- Monitor and maintain the performance of deployed models.
- Work closely with engineering teams to integrate machine learning solutions into existing systems.
- Troubleshoot and resolve issues related to model performance and infrastructure.
Required Skills & Qualifications:
- Strong experience in MLOps and machine learning engineering principles.
- Proficiency in programming languages such as Python or Java.
- Experience with machine learning frameworks like TensorFlow or PyTorch.
- Familiarity with cloud platforms such as AWS or Azure.
- Understanding of data pipelines and ETL processes.
- Excellent problem-solving skills and ability to work in a collaborative environment.
The ideal candidate will have a proven track record of deploying machine learning models at scale and a strong understanding of both data science and software engineering principles.
What we offer:
- Opportunity to work on cutting-edge technologies in a dynamic environment.
- Collaborative team culture that encourages innovation and professional growth.
- Access to ongoing training and development resources.
This role is managed by AI-First Talent on behalf of our client. Your application is reviewed directly by our talent team.