Data MLOps Engineer

TechDigital

Providence, RI
Today

Highlights

Data MLOps Engineer Experience working within the Azure ecosystem, including Azure AI Search, Azure Storage Blob, Azure Postgres and understanding how to leverage them for data processing, storage, and analytics tasks. Be able to implement efficient data processing workflows to support the training and evaluation of solutions using large language models, ensuring reliability, scalability, and performance.

Numbers & Facts

Location	Providence, RI
Industry	Other/Not Classified
Company Size	100 to 499 employees

Description

Data MLOps Engineer

Experience working within the Azure ecosystem, including Azure AI Search, Azure Storage Blob, Azure Postgres and understanding how to leverage them for data processing, storage, and analytics tasks.
Ability to preprocess and clean large datasets efficiently using Azure Tools /Python and other data manipulation tools. Experience with techniques such as data normalization, feature engineering, and data augmentation is preferred.
To have background in Data Science/MLOps and proficiency in DevOps, CI/CD, Azure Cloud computing and Model monitoring.
Expertise in working with healthcare data standards (ex. HIPAA and FHIR), sensitive data and data masking techniques to mask personally identifiable information (PII) and protected health information (PHI) is essential.
In-depth knowledge of search algorithms, indexing techniques, and retrieval models for effective information retrieval tasks. Familiarity with search platforms like Elasticsearch or Azure AI Search is a must.
Familiarity with chunking techniques and working with vectors and vector databases like Pinecone.
Ability to design, develop, and maintain scalable data pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data.
Experience with implementing best practices for data storage, retrieval, and access control to ensure data integrity, security, and compliance with regulatory requirements.
Be able to implement efficient data processing workflows to support the training and evaluation of solutions using large language models, ensuring reliability, scalability, and performance.
Ability to proactively identify and address issues related to data quality, pipeline failures, or resource contention, ensuring minimal disruption to systems.
Experience with large language model frameworks, such as Langchain and know how to integrate them into data pipelines for natural language processing tasks.
Experience working within the snowflake ecosystem.
Knowledge of cloud computing principles and experience in deploying, scaling, and monitoring AI solutions on cloud platforms like Snowflake, Azure, AWS.
Ability to communicate complex technical concepts effectively to technical and non-technical stakeholders and collaborate with cross-functional teams.
Analytical mindset with a keen attention to detail, coupled with the ability to solve complex problems efficiently.
Knowledge of cloud cost management principles and best practices to optimize cloud resource usage and minimize costs.

Must Have:

Minimum of 10 years' experience as a data engineer
Hands-on experience with Azure Cloud eco-system.
Hands-on experience using Python for data manipulation.
Deep understanding of vectors and vector databases.
Hands-on experience scaling POC to production.
Hands-on experience using tools such as Document Intelligence, Snowflake, function app. Azure AI Search
Experience working with PII/PHI
Hands-on experience working with unstructured data.

Similar Jobs

Michael Page USA

Senior Mechanical Engineer - Industrial - Providence, RI

Providence, RI

10 days ago

See more jobs