Our client, a multinational telecommunications technology company, has an urgent and immediate need for an experienced Machine Learning Engineer to work onsite in Plano, TX.

The ideal candidate will bring a strong blend of Machine Learning Engineering and hands-on Data Engineering expertise, with experience building scalable, production-grade data pipelines and supporting enterprise ML workflows. This role focuses heavily on post-ingestion data processing, ML enablement, workflow orchestration, and advanced data modeling.

Key Responsibilities
- Design, develop, and maintain production-grade data pipelines and ML workflows.
- Build scalable solutions using Python, PySpark, Databricks, and Spark.
- Develop and support APIs and ML workflow integrations.
- Work with large-scale distributed data systems including Kafka, Snowflake, MongoDB, PostgreSQL, and Redis.
- Implement advanced SQL and NoSQL data models, including slowly changing dimensions (SCD) and temporal mapping strategies.
- Support data migrations involving identifier remapping and historical backfills.
- Utilize Delta Lake and MLflow to support model lifecycle management and data versioning.
- Develop and manage workflow orchestration processes for ML and data engineering pipelines.
- Collaborate with cross-functional engineering and data science teams in an Azure cloud environment.
- Monitor and troubleshoot platform performance using ELK (Elastic/Kibana) tools.
- Contribute to GenAI-related initiatives and next-generation AI solutions where applicable.


If you would like to learn more, please reach out to ELite Technical.

Required Skills

Required Skills:

- 5 to 8 years Experience
- Experience building production-grade data pipelines,
- Solid Python skills with APIs development and familiarity with ML workflows.
- Delta Lake, MLflow, and workflow orchestration experience.
- Migrations involving identifier remapping or historical backfills.
- GenAI experience will be a big plus
- Familiarity with ELK (Elastic Kibana)