Machine Learning Engineering Lead (100% Remote, 12-month Contract)
Remote
AI Summary
Lead Machine Learning Engineering projects, design and implement data architectures, and develop scalable workflows. 7+ years of experience in ML engineering and data engineering required. Strong Python and SQL skills needed.
Key Highlights
Lead Machine Learning Engineering projects
Design and implement data architectures
Develop scalable workflows
Technical Skills Required
Benefits & Perks
100% remote work
12-month contract with potential extension
Job Description
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Sriven Systems Inc., is seeking the following. Apply via Dice today!
Role: ML Engineering
100% REMOTE 12 month contract with strong potential of extension
You must be able to go onsite for technical round interview in Plano, TX
Top Skills' Details
Leadership & Technical Expertise:
must have extensive Machine Learning Engineering experience along with Azure, Databricks, Medallion, Delta Lake, and MLFlow experience.
5 7 years of handson ML engineering and data engineering experience, including building and hydrating curated data models and leading technical teams.
Proven ability to design MLready data architectures and establish engineering standards, coding practices, and scalable workflows.
Deep understanding of Medallion Architecture, including how to ingest raw source data into Bronze, refine and validate it in Silver, and deliver clean, conformed, analytics and MLready Gold Layer datasets.
Azure Databricks:
Extensive experience using Azure Databricks for ML development, feature engineering, and data engineering pipelines.
Background migrating workloads to Databricks and leveraging Delta Lake, MLflow, and Databricks Workflows to operationalize ML and data transformations.
Python & SQL:
Strong proficiency in Python for model development, feature engineering, and MLOps automation.
Advanced SQL skills to build transformations, views, and optimized ELT pipelines that hydrate the Gold Layer.
Comfortable working in a fastpaced, collaborative environment where experimentation and iteration are encouraged.
Data & Analytics Background:
10+ years in Data & Analytics, delivering enterprisescale data and ML solutions.
Experience designing feature stores, MLready semantic layers, and productiongrade data assets.
Ability to integrate ML outputs into analytics tools and businessfacing dashboards.
Analytics & Visualization:
Experience designing semantic models and dashboards to surface ML insights, data quality metrics, and model performance.
Familiarity with Power BI best practices, including DAX and visualization standards.
Secondary Skills - Nice To Haves
- Statistical model
- Tensorflow
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