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MLOps Engineer | Austin, TX (Onsite from Day 1) at Austin, Texas, USA
Email: [email protected]
Hello,

Hope you are doing great.

Job Title : MLOps Engineer

Client : Apple/Tech Mahindra

Location : Austin, TX (Onsite from Day 1)

Contract

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 fine-tuning of LLMs.

    Monitor and improve the scalability and latency of LLM deployments.

Qualifications:

Education:

Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

Experience:

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

        Hands-on 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

Thanks & Regards,

Irfan Shaik

P : 972-440-0069

Cell No: 647-375-2228

Agile Enterprise
Solutions Inc.

2591 Dallas Parkway,Suite 300, Frisco,TX 75034.

Email: 

[email protected] 

 Website:

www.aesinc.us.com

Keywords: continuous integration continuous deployment machine learning information technology Texas
MLOps Engineer | Austin, TX (Onsite from Day 1)
[email protected]
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Tue Jul 30 02:40:00 UTC 2024

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Location: Austin, Texas