Machine Learning Engineer

Alliance Advanced Inc.; Fresno (CA); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Comprehensive health insurance

Retirement plan with employer matching

Opportunities for professional dev

Job summary

Alliance Advanced Inc. in Fresno, CA is seeking a full-time Machine Learning Engineer to build and deploy models that address complex business problems.

You will design, train, and optimize models, perform data preprocessing, and collaborate with data scientists, software engineers, and business analysts to integrate ML solutions into existing systems. You will evaluate models with metrics such as cross-validation and ROC curves, and help bring models into production via APIs and user

Qualifications

• Master's degree in Computer Science, Electrical Engineering, or a related field.
• 2+ years of experience in machine learning and data science.
• Proficiency in Python and ML libraries such as TensorFlow, PyTorch, or Scikit-learn.
• Knowledge of cloud platforms like AWS or GCP is a plus.

Responsibilities

• Develop and deploy machine learning models to improve products and services.
• Collaborate with cross-functional teams to translate business needs into technical requirements.
• Conduct data analysis and preprocessing to ensure high-quality input for models.

Skills

Machine learning

Data analysis

Cross-functional collaboration

Education

Master's degree in Computer Science or related field

Bachelor's degree in Computer Science, Statistics, or Mathematics

Tools

Python

TensorFlow

scikit-learn

PyTorch

AWS

GCP

Job description

Position Overview

Alliance Advanced Inc. is hiring a Machine Learning Engineer in Fresno, CA, for a full-time position. You will develop and implement machine learning models to solve complex problems and drive innovation. The salary is negotiable, and the position is valid until November 23, 2026.

Your day-to-day tasks will involve designing and training machine learning models, which may include tasks such as feature engineering, data preprocessing, and model selection. You will also optimize algorithms to improve their efficiency and performance, which may involve techniques such as hyperparameter tuning, algorithm selection, and model pruning. Additionally, you will evaluate model performance using appropriate metrics and techniques, such as cross-validation, confusion matrices, and ROC curves. You will also collaborate with cross-functional teams, such as data engineers, software developers, and business analysts, to integrate machine learning solutions into existing systems. This may involve tasks such as designing APIs, developing user interfaces, and ensuring that the machine learning solutions meet the needs of the business.

You will work in a team of data scientists and engineers in Fresno, CA. The workplace is in California, and you will be part of a collaborative environment focused on advancing machine learning technologies.

Key Responsibilities

• Develop and deploy machine learning models to improve our products and services
• Collaborate with cross-functional teams to understand business needs and translate them into technical requirements
• Conduct data analysis and preprocessing to ensure high-quality input for machine learning models
• Monitor and maintain machine learning models in production to ensure optimal performance
• Stay up-to-date with the latest advancements in machine learning and data science

Benefits

• Comprehensive health insurance
• Retirement plan with employer matching contributions
• Opportunities for professional development through workshops, conferences, and online courses

Requirements & Qualifications

• Master's degree in Computer Science, Electrical Engineering, or a related field
• Experience with Python, TensorFlow, and scikit-learn is required
• Knowledge of cloud platforms like AWS or GCP is a plus
• Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field
• 2+ years of experience in machine learning and data science
• Proficiency in Python and experience with machine learning libraries such as TensorFlow, PyTorch, or Scikit-learn
• Strong understanding of statistical concepts and machine learning algorithms
• Experience with cloud platforms such as AWS or GCP is a plus