MLOps Engineer at Austin TXOnsite

Hi

Hope you are doing well !! My name is Arun from Siri Info Solutions. I am sharing one urgent job opportunity with you kindly go through it and let me know if suitable for you.

Title: MLOps Engineer

Location: Austin TX/Onsite

Duration : Contract Role

Job Description:

We are seeking a skilled and motivated MLOps Engineer to join our dynamic team. The ideal candidate will be responsible for developing implementing and maintaining machine learning pipelines and infrastructure ensuring the efficient and reliable deployment of ML models into production environments. You will collaborate closely with data scientists software engineers and IT professionals to optimize and automate the machine learning lifecycle.

Key Responsibilities:

Design implement and manage scalable ML model deployment pipelines.

Automate the deployment process using CI/CD tools.

Monitor troubleshoot and maintain deployed models in production.

Develop and maintain infrastructure for data ingestion processing and storage. Optimize compute resources for cost and performance efficiency.

Ensure high availability and scalability of ML infrastructure.

Provide support for model retraining and updates.

Implement monitoring and logging solutions for model performance and data quality.

Optimize the performance of large language models (LLMs) in production environments.

Implement techniques for efficient inference and finetuning of LLMs.

Monitor and improve the scalability and models in production.

Develop and maintain infrastructure for data

ingestion processing and storage. Optimize compute resources for cost and performance efficiency.

Ensure high availability and scalability of ML infrastructure.

Provide support for model retraining and updates.

Implement monitoring and logging solutions for model performance and data quality.

Optimize the performance of large language models (LLMs) in production environments.

Implement techniques for efficient inference and

finetuning of LLMs.

Monitor and improve the scalability and latency of LLM deployments.

Education:

Bachelors or Masters degree in Computer Science Engineering or a related field.

Experience:

Proven experience as an MLOps Engineer or in a similar role.

Handson experience with ML model deployment and lifecycle management.

Proficiency in programming languages such as Python Java.

Experience with ML frameworks such as TensorFlow PyTorch.

Familiarity with containerization and orchestration tools (Docker Kubernetes).

Experience with cloud platforms (AWS GCP Azure).

Experience with large language models (LLMs) and their performance optimization.

Best Regards

Arun Bansal

Technical Recruiter

D : Email: