Lead ML/ Ops Engineer

Miami, FL

Onsite  -  DevOps  -    -  Job ID: 23-71998

Location: Miami, FL 3-4 day onsite
Contract : 6 mths
Pay Rate: 75.00 w2 80.00 C2C
USC or Green Card holder

Lead ML/Ops Engineer

The ML Engineering is responsible for architecting the productionalized solution around rules-based and AI/ML models to integrate predictions seamlessly into the business processes, ensuring governance, resiliency, explainability, reproducibility, and scalability of the models. We are looking for a highly capable ML Platform Engineer to optimize rules-based and machine learning systems. As an engineer for the ML platform you will be working at the intersection of machine learning, DevOps, and data engineering (i.e. MLOps). The position will require.

ML Platform Engineer Responsibilities:
Lead and consult with business stakeholders and data science teams to define data engineering and MLOps requirements.
Transforming business and data science prototypes and applying appropriate algorithms and tools.
Solving complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries and frameworks.
Developing reusable data and feature stores for rules-based and AI/ML models.
Developing alerting tool frameworks for monitoring productionized model performance and effectiveness.
Automate deployments incorporating MLOps best practices into productionalized solutions.
Document frameworks and machine-learning processes.
Required Skills
Experience building scalable machine learning systems and data-driven products working with cross-functional teams.
Well-developed software engineering fundamentals, including use of proper development, QA, and production environments, and the ability to write production-level code when needed.
Experience creating a python package
Proficiency in Python and experience with common data analytics packages (e.g. Numpy, Pandas, Sklearn, PySpark).
Proficiency in Databricks & MLFlow
Proficiency in SQL.
Good communication skills and the ability to understand and synthesize requirements across multiple project domains.
Works effectively with cross-functional teams.

Required Education
Bachelor's degree in computer science, data science, mathematics, or a related field.
Required Years of Experience
5+ years of overall experience in Data Analytics.
2+ years of experience with ML Engineering and/or ML Ops.
Desired Skills
Experience with Agile Software Development.
Experience in a large corporation or consulting firm
Experience with IoT and/or sensor data.

Desired Education
Masters or PhD degree in computer science, data science, mathematics, or a related field.
Desired Years of Experience
7+ years of overall experience in Data Analytics.