Machine Learning Engineer

  • Cary, NC
  • Posted 42 days ago | Updated 10 days ago

Overview

Hybrid
Depends on Experience
Full Time

Skills

Machine Learning
ML Engineer
Python
Nvidia
TensorFlow
PyTorch
Azure
AWS
GCP
cloud platforms
CI/CD
MLOps
model deployment
containerization
Docker
SQL
NoSQL
data pipelines
feature engineering
hyperparameter tuning
model optimization
data preprocessing
machine learning models
risk evaluation
version control
Git
automated testing
Agile
Scrum
data analysis
data structuring
model monitoring
performance tracking
data drift detection
troubleshooting
sprint planning
documentation
technical communication
ETL processes
pipeline optimization
Apache Spark
distributed computing

Job Details

Please, no third parties. Permanent residents only.
This is a direct-hire or contract-to-hire opportunity.


Main Duties & Responsibilities:
- Design, construct, and fine-tune machine learning models using Python, Nvidia frameworks, and other relevant technologies to tackle diverse challenges such as risk evaluation and customer profiling.
- Apply advanced techniques in feature engineering, hyperparameter tuning, and performance optimization to enhance model effectiveness.
- Work alongside the team to establish CI/CD workflows for seamless deployment of ML models within Azure cloud infrastructure.
- Manage the full model lifecycle, incorporating version control, containerization, and automated deployment methodologies.
- Collaborate with Data Engineers to develop well-structured, high-quality data pipelines for model training and evaluation.
- Utilize SQL and other database tools to preprocess, clean, and structure data sets for analysis.
- Implement robust monitoring systems to track model accuracy, performance, and potential data drift.
- Diagnose issues in deployed models and optimize them to maintain consistency and reliability.
- Engage with actuarial teams, underwriting experts, and business stakeholders to translate business objectives into AI-driven solutions.
- Contribute to Agile development processes, including sprint planning, daily stand-ups, and retrospective discussions.
- Maintain comprehensive documentation covering model design, data workflows, and deployment protocols.
- Effectively convey insights and project updates to both technical and non-technical audiences.

Skills & Requirements:
- Bachelors Degree or higher in Computer Science, Data Science, Engineering, or a related field is highly preferred.
- 3+ years of hands-on experience in machine learning within a production setting.
- Strong proficiency in Python and deep learning frameworks such as TensorFlow and PyTorch.
- Hands-on experience with Azure or other cloud platforms (AWS, Google Cloud Platform) for deploying machine learning models.
- Knowledge of SQL, NoSQL, or similar database technologies.
- Understanding of MLOps best practices, including CI/CD automation and containerization (Docker).
- Familiarity with Agile development practices, including Scrum methodologies.
- Experience with version control systems like Git and automated testing frameworks.
- Strong communication skills with the ability to collaborate effectively in team environments.
- Analytical mindset with a keen attention to detail and problem-solving abilities.
- Knowledge of ETL processes and data pipeline optimizations. Experience with distributed computing frameworks like Apache Spark.



tags: senior machine learning engineer, senior ml engineer, senior data engineer, senior data analyst, senior business intelligence engineer, senior bi engineer, senior mlops engineer, senior cloud data engineer

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