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Machine Learning Intern AI and Automation

Calix Anywhere

Live

$49k - $90k · Senior Full-time Posted about 2 months ago 5 min read

Summary: • You should be pursuing a relevant degree, have strong math/statistics skills, Python proficiency, ML knowledge, and experience with Git, Unix, big data, cloud platforms, MLOps, and NLP. • You will design and implement ML algorithms, evaluate model performance, fine-tune models with TensorFlow/PyTorch, assist in generative AI development, and document technical specifications.

This is a remote position that can be based anywhere in the United States or Canada.

Calix is looking for a Machine Learning intern with a strong foundation in ML fundamentals and algorithms to join our Products Team for the Summer. In this role, you will be part of a unique and award-winning internship program within the company. The program provides the opportunity to learn new skills through training and on the job learning.

In this role, you will work on developing and implementing sophisticated machine learning solutions, including both traditional ML models and cutting-edge generative AI applications. You'll have the opportunity to work with large-scale datasets and contribute to the entire ML pipeline, from data preprocessing to model deployment.

Responsibilities and Duties: • Design and implement machine learning algorithms for various applications, including classification, regression, and clustering problems • Conduct thorough model evaluation, validation, and performance optimization using industry-standard metrics • Implement and fine-tune various ML models using frameworks such as TensorFlow, PyTorch, and Scikit-learn • Assist in the development of generative AI applications using state-of-the-art models • Document model architectures, experimental results, and technical specifications

Required Qualifications: • Currently pursuing a Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or a related technical field. Preference will be given to students with prior work experience • Strong foundation in mathematics and statistics, including: • Linear algebra and calculus • Probability theory and statistical modeling • Optimization techniques • Proficiency in Python programming with experience in ML libraries and frameworks • Understanding of fundamental machine learning concepts: • Supervised and unsupervised learning algorithms • Model evaluation and validation techniques • Feature engineering and selection methods • Experience with version control systems (Git) and data processing tools • Experience with Unix-based OS • Able to work for the complete summer break (May - August or June - September)

Preferred Qualifications: • Previous coursework or projects in machine learning, deep learning, or AI • Experience with big data technologies such as Apache Spark • Familiarity with cloud platforms (AWS, Google Cloud) and their ML services • Knowledge of MLOps practices and model deployment workflows • Understanding of deep learning architectures and their applications • Experience with Natural Language Processing (NLP) concepts and techniques

Location: • Remote-based position located in the United States or Canada.

LI-Remote

Compensation will vary based on geographical location (see below) within the United States. Individual pay is determined by the candidate's location of residence and multiple factors, including job-related skills, experience, and education.

There are different ranges applied to specific locations. The average base pay range (or OTE range for sales) in the U.S. for the position is listed below.

San Francisco Bay Area Only:

27.60 - 34.50 USD Hourly All Other Locations:

24.00 - 30.00 USD Hourly

About Us

PLEASE NOTE: All emails from Calix will come from a '@calix.com' email address. Please verify and confirm any communication from Calix prior to disclosing any personal or financial information. If you receive a communication that you think may not be from Calix, please report it to us at talentandculture@calix.com .

Calix delivers a broadband platform and managed services that enable our customers to improve life one community at a time. We’re at the forefront of a once in a generational change in the broadband industry. Join us as we innovate, help our customers reach their potential, and connect underserved communities with unrivaled digital experiences.

This is the Calix mission - to enable CSPs of all sizes to Simplify. Innovate. Grow.

If you are a person with a disability needing assistance with the application process please: • Email us at calix.interview@calix.com ; or • Call us at +1 (408) 514-3000.

Calix is a Drug Free Workplace.

Requirements: • Currently pursuing a Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or a related technical field. Preference will be given to students with prior work experience • Strong foundation in mathematics and statistics, including: • Linear algebra and calculus • Probability theory and statistical modeling • Optimization techniques • Proficiency in Python programming with experience in ML libraries and frameworks • Understanding of fundamental machine learning concepts: • Supervised and unsupervised learning algorithms • Model evaluation and validation techniques • Feature engineering and selection methods • Experience with version control systems (Git) and data processing tools • Experience with Unix-based OS • Able to work for the complete summer break (May - August or June - September) • Previous coursework or projects in machine learning, deep learning, or AI • Experience with big data technologies such as Apache Spark • Familiarity with cloud platforms (AWS, Google Cloud) and their ML services • Knowledge of MLOps practices and model deployment workflows • Understanding of deep learning architectures and their applications • Experience with Natural Language Processing (NLP) concepts and techniques

Responsibilities: • Design and implement machine learning algorithms for various applications, including classification, regression, and clustering problems • Conduct thorough model evaluation, validation, and performance optimization using industry-standard metrics • Implement and fine-tune various ML models using frameworks such as TensorFlow, PyTorch, and Scikit-learn • Assist in the development of generative AI applications using state-of-the-art models • Document model architectures, experimental results, and technical specifications

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