Job Title: Senior Machine Learning Engineer
Location: Dallas TX /Richardson TX (Hybrid)
Duration: Long Term
Job Description:
We are seeking a highly skilled and experienced Machine Learning Engineer with expertise in scaling and deploying complex ML models preferably on Kubernetes using opensource ML frameworks. The ideal candidate will have a strong background in machine learning and DevOps/MLOps practices.
Key Responsibilities:
Develop train and deploy scalable machine learning models using frameworks such as TensorFlow PyTorch and Scikitlearn.
Design and implement ML model deployment pipelines on Kubernetes clusters.
Optimize ML algorithms for performance and scalability.
Collaborate with data engineers to build and maintain efficient data pipelines for model training and inference.
Implement CI/CD pipelines for ML workflows to ensure seamless model deployment and updates.
Monitor and maintain the health performance and reliability of deployed ML models.
Work closely with crossfunctional teams to integrate ML models into production applications.
Stay uptodate with the latest developments in machine learning Kubernetes and opensource technologies.
Qualifications:
10 years of experience in machine learning.
Prior experience in a production environment with largescale ML deployments
Proven experience with Kubernetes and container orchestration.
Strong proficiency in opensource ML frameworks such as TensorFlow PyTorch and Scikitlearn.
Experience with CI/CD tools and practices particularly for ML workflows.
Proficiency in programming languages such as Python and familiarity with libraries and tools for data manipulation and analysis.
Familiarity with cloud platforms such as AWS GCP or Azure.
Excellent problemsolving skills and the ability to work in a fastpaced dynamic environment.