AI / MLOps Lead - Onsite - Austin, TX

Job ID: SRJ_7203Location: Austin, TXSalary: USD 64-65 / Hourly (C2C)Employment Type: C2C, Full TimeCompany: SRI Tech SolutionsJob Title:AI / MLOps LeadLocation:Austin, TX ,USASkillsAI/ML EngineeringExperience (Years)6 (Min) - 10 (MaxJob DescriptionWe 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.ResponsibilitiesTechnical 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 supportCollaboration:Work closely with internal and client side stakeholders to address problems and implement best practices.QualificationsBachelors or Masters degree in Computer Science, Engineering or related field8+ 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 platformsUnderstanding 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 modelSRI Tech Solutions is an equal opportunity employer and does not discriminate on the basis of race, color, gender, religion, age, sexual orientation, national origin or citizenship status or ethnic origin, disability, marital status, veteran status, or any other occupationally irrelevant criteria.