Machine Learning Engineer

The ML Engineer will bridge the gap between Data Scientists and Data Engineers. He/she will own the implementation of ML models developed by Data Scientists, ensuring a seamless and efficient transition from model prototyping to production deployment. They collaborate closely as well with the MLOps Engineer, responsible for managing infrastructure, continuous integration, deployment, scalability, security, and overall operational aspects of machine learning systems.  

The project is scheduled to run over the course of six months, with a start and end date to be determined. Additionally, there is the potential for its later incorporation as a Full-Time Equivalent (FTE). This includes development, testing, and implementation phases for each deliverable. Regular status updates and checkpoints will be scheduled to ensure alignment with project milestones. Candidate must be available to start immediately.

• Large Language Models Implementations - Deploy Large Language Models into production using best practices for version control, lineage tracking, and proper governance. 
• Backfilling with Large Language Models - Collaborate in the design, implement, and execute Backfilling procedures to enrich our historical data. 
• LLM Assistant - Collaborate with the Backend (BE) team to seamlessly integrate LLM Assistant functionalities into the existing infrastructure. Provide technical support and expertise. 
• Documentation - Provide detailed documentation for the deployed LLMs, integration processes, and monitoring mechanisms. Include troubleshooting guides and best practices for ongoing maintenance. 

• Experience working with Large Language Models (LLMs) in production environments. 
• Over 4 years of proven experience as a Machine Learning Engineer or in a comparable role. 
• Solid understanding of machine learning concepts, algorithms, and methodologies. 
• Proficient in English with effective communication skills. 
• Teamwork spirit and a Proactive "can-do" attitude. 

• Advanced proficiency in Python. 
• Expertise in PySpark and Ray. 
• Familiarity with Databricks environment. 
• Proficient use of MLFlow for effective model management and deployment. 

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Edelman Data & Intelligence (DXI) is a global, multidisciplinary research, analytics and data consultancy with a distinctly human mission.

We use data and intelligence to help businesses and organizations build trusting relationships with people: making communications more authentic, engagement more exciting and connections more meaningful.

DXI brings together and integrates the necessary people-based PR, communications, social, research and exogenous data, as well as the technology infrastructure to create, collect, store and manage first-party data and identity resolution. DXI is comprised of over 350 research specialists, business scientists, data engineers, behavioral and machine-learning experts, and data strategy consultants based in 15 markets around the world.

To learn more, visit: https://www.edelmandxi.com

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