Job Description :

Hi,

Hope you are doing well,

Please find the job description given below and let me know your interest.

Position: ML Engineer with Strong MLOps, LLMOps Experience

Location: Hybrid 3x/week onsite in Malvern, PA----Relocation Will Work

Duration: 12+ months

Job Description:

Responsibilities

Own the end-to-end Machine Learning Pipeline together with CI/CD for our ML Engineering and Productionization process. Focus on code, versioning of datasets, models and production endpoints to allow ML Engineers to collaborate, experiment and scale fast.

Qualifications

Develop end-to-end (Data/Dev/ML)Ops pipelines based on in-depth understanding of cloud platforms, AI lifecycle, and business problems to ensure analytics solutions are delivered efficiently, predictably, and sustainably.

Implement model monitoring

Productionize GenAI Applications

Bring your deep expertise in cloud architecture / DevOps to analyze and recommend enterprise-grade solutions for operationalizing AI / ML analytics.

Build and automate our AI/ML workstream from data analysis, experimentation, operationalization, model training, model tuning to visualization.

Improve and maintain our automated CI/CD pipeline.

Assist data scientists with model evaluation and training (includes versioning, compliance and validation).

Build and maintain data pipelines for analytics, model evaluation and training (includes versioning, compliance and validation).

Work with AI/ML practitioners to solve complex problems and create unique solutions for MLOps.

Continuously evaluate the latest packages and frameworks in the ML ecosystem

Experience in configuring AWS environment (i.e. EC2, S3, DB's etc.) Data(Glue, EMR,etc.) and AWS Services (Step & Lambda Functions etc.)

Familiarity with container technologies including AWS Fargate, Docker and Kubernetes

Proficient in AWS, DevOps, CI/CD and Microservices

Expert in Container technologies like Kubernetes and Docker

Experience developing and managing packages and APIs using Python

Expertise in developing and deploying ML models in AWS Sagemaker

Continuous Integration for Machine Learning projects.

Continuous Delivery for Machine Learning projects.

Improve and advance DataOps and MLOps infrastructure and operational processes.

Please share your updated resume and suggest the best number & time to connect with you

,

Raveena Mourya
US IT Recruiter, DMS Visions Inc

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4645 Avon Lane, Suite 210, Frisco, TX 75033

             

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