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Jobs or company...

Machine Learning (ML) Engineer

Salary undisclosed

Apply on

Dice

Availability Status

This job is expected to be in high demand and may close soon. We’ll remove this job ad once it's closed.

Original
Simplified

Machine Learning (ML) Engineer

Las Vegas, Nevada (Hybrid)

Long term contract

The Machine Learning (ML) Engineer is an expert in developing and implementing machine learning algorithms and models, focusing on solving complex business problems and enhancing technological solutions within the organization.

The candidate must demonstrate substantial background and passion for machine learning, AI, and statistical modeling.

Essential Duties & Responsibilities

  • Architect and build robust cloud-based pipelines and robust ML framework to train, deploy, infer and monitor machine learning models at scale.
  • Apply expertise in model design, training, evaluation, validation, implementation, and monitoring.
  • Conduct data preprocessing, feature engineering, and model evaluation.
  • Manage workflows and data pipelines.
  • Implement monitoring systems to track how models are performing.
  • Design, develop, and implement predictive models and algorithms to support business objectives.
  • Conduct exploratory data analysis, descriptive analysis and deep dives, and examine large datasets to uncover trends, patterns, and opportunities for business improvement.
  • Incorporate visualization techniques to support the relevant points of the analysis and ease the understanding for less technical audiences.
  • Formulate infrastructure decisions using understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation.
  • Create and maintain detailed documentation for operational execution.
  • Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI.
  • Drive code reviews to help team adhere to general best practices.
  • Provide technical guidance and mentorship to other team members.
  • Innovate with new approaches, staying abreast of current research and latest technologies in the broader ML engineering community.

Minimum Qualifications

  • Bachelor's degree in computer science, engineering, data science, statistics, mathematics, or a related field. Master's degree preferred.
  • Must be able to obtain and maintain Nevada Gaming Control Board registration and any other certification or license, as required by law or policy.
  • A minimum of 2 years of relevant experience.
  • Practical experience in building, evaluating, scaling, and deploying machine learning pipelines with Python, preferably within the Google Cloud Platform and Databricks ecosystem
  • Programming skills in Python and fluency in data manipulation (SQL, Spark, Pandas) and machine learning (e.g.: scikit-learn, Keras/Tensorflow, etc.) and optimization (e.g. linear programming) tools.
  • Experience with CI/CD pipelines, and Git version control.
  • Experience with data visualization to convey ML models behavior and business insights.
  • Demonstrated experience in statistical and/or quantitative analysis, forecasting, predictive analytics, multivariate testing, outlier analysis and/or optimization algorithms.
  • Expertise in AI/ML model design and development, frameworks, and libraries such as TensorFlow, PyTorch, scikit-learn, Pandas, NumPy, NLTK or spaCy, OpenCV or similar.
  • Experience working with large, dynamic data sets and developing code to ingest, cleanse, and evaluate data.
  • Solid understanding of Machine Learning fundamentals and ability to translate business requirements into machine learning solutions.

Regards,

Ayush Sharma

Sr. US IT Recruiter

| Ext:149

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Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
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