Overview
On Site
Full Time
Skills
Python
databricks
Mlops
Tensorflow
Job Details
Fulltime Opportunity
Role: AI/MLOps Lead
Location: Austin, TX
Type: FTE
Job Description
We are seeking a Tech Lead for a support related role for deployed ML solutions. You'll act as a bridge between the client and the offshore team ensuring timely resolution of support incidents, implementation and deployment of change requests as well as finding avenues for automation in order to reduce effort.
Responsibilities
- Technical Support: Provide technical support for production machine learning models, including troubleshooting and resolving ML pipeline issues, model performance degradation, data anomalies, and deployment failures.
- Shift: You should be willing to work on a shift based schedule and should be ready to provide on call weekend support
- Collaboration: Work closely with internal and client side stakeholders to address problems and implement best practices.
Qualifications
- 8+ years of experience in machine learning engineering, including deploying, maintaining, and troubleshooting ML models in production.
- Experience in leading a team, client interaction and reporting.
- Strong hands on experience with Python and ML frameworks (TensorFlow, PyTorch, Scikit learn, etc.).
- Strong hands on experience with Databricks for building, deploying, and managing machine learning workflows.
- Hands on with MLOps tools and cloud platforms
- Understanding of CI/CD for ML workflows.
- Proven problem solving skills, especially in diagnosing and resolving issues in large scale, distributed ML systems.
- Strong understanding of data engineering concepts, pipeline orchestration, and model versioning.
- Knowledge of model
Thanks &Regards
Rahul Sharma | Talent Acquisition Specialist
Amaze Systems Inc
E: |
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.