Associate Machine Learning Engineer

T-Mobile • Bellevue, WA

2d

About The Position

The Associate Machine Learning (ML) Engineer at T-Mobile is instrumental in advancing our AI-driven initiatives. This role focuses on supporting the design, development, and deployment of machine learning models that enhance our customer interactions and operational efficiency. By leveraging data-driven insights and modern ML frameworks, the engineer contributes to innovation and helps integrate AI technologies into T-Mobile’s products and services. Working closely with senior ML engineers, data scientists, and cross-functional engineering teams, this role provides an opportunity to gain hands-on experience with end-to-end ML pipelines, big data platforms, and cloud technologies while learning industry best practices. We pride ourselves on encouraging a culture of innovation, advocating for agile methodologies, and promoting transparency in all that we do. Join us in embodying the spirit of the 'Un-carrier' and make a tangible impact! Our team is dynamic where no day is the same, and we are diverse and inclusive passionate about growth and transformation. If you're up to the challenge, apply today!

Requirements

• Bachelor's Degree in Computer Science, Engineering, Statistics, Informatics, Information Systems, Machine Learning, or another quantitative field (Required).
• Experience in developing or deploying ML models (academic, internship, or professional experience acceptable).
• Machine Learning & Deep Learning: Solid understanding of classic supervised and unsupervised machine learning algorithms (e.g., classification, clustering, regression, SVM) (Required)
• Data Engineering & Platforms: Proficiency in data manipulation and analysis using Apache Spark, Databricks, and Snowflake for big data processing (Required).
• Working knowledge of SQL for querying and managing databases (Preferred).
• Programming: Proficiency in Python or R (Required).
• Mathematics & Statistics: Strong foundation in probability, statistics, and mathematics (Required).
• Collaboration & Communication: Ability to work in cross-functional teams to integrate AI technologies into production (Required).
• Strong problem-solving and analytical skills to troubleshoot ML solutions (Required).

Nice To Haves

• Master's/Advanced Degree in Computer Science, Machine Learning, Data Science, or a related field (Preferred).
• Experience with cloud technologies for model training and deployment (Preferred).
• Familiarity with deep learning architectures (LSTM, CNNs) and LLMs (Preferred).
• Knowledge of ML frameworks like TensorFlow, Keras, and PyTorch as well as MLOps tools (Preferred).
• Experience with containerization and orchestration tools (Docker, Kubernetes) (Preferred).
• Strong knowledge of software engineering principles: version control, testing, CI/CD. (Preferred)
• Familiarity with Agile practices for iterative development (Preferred).
• Excellent communication skills to collaborate with technical and non-technical teams (Preferred).

Responsibilities

• Assist in designing, developing and refining machine learning models to enhance customer interactions and operational efficiency.
• Support data preparation, training, testing, and evaluation for ML and deep learning models.
• Build and maintain data pipelines for large-scale training and inference
• Optimize model performance, including feature engineering, hyperparameter tuning, and algorithm selection.
• Work with large language models (LLMs) and leverage ML frameworks for training, testing and evaluation.
• Collaborate with data scientists and engineering teams to integrate ML models into production systems and ensure scalability.
• Utilize platforms such as Databricks, Snowflake, and Apache Spark to build and manage ML pipelines.
• Support the development of end-to-end model training pipelines using TensorFlow, Keras, PyTorch, HuggingFace and TensorBoard for visualization.
• Leverage containerization and orchestration tools (Docker, Kubernetes)
• Stay updated with the latest AI/ML research, tools, and technologies to enhance development practices.

Benefits

• Employees enjoy multiple wealth-building opportunities through our annual stock grant, employee stock purchase plan, 401(k), and access to free, year-round money coaches.
• employees in regular, non-temporary roles are eligible for an annual bonus or periodic sales incentive or bonus, based on their role.
• Most Corporate employees are eligible for a year-end bonus based on company and/or individual performance and which is set at a percentage of the employee’s eligible earnings in the prior year.
• medical, dental and vision insurance, a flexible spending account, 401(k), employee stock grants, employee stock purchase plan, paid time off and up to 12 paid holidays - which total about 4 weeks for new full-time employees and about 2.5 weeks for new part-time employees annually - paid parental and family leave, family building benefits, back-up care, enhanced family support, childcare subsidy, tuition assistance, college coaching, short- and long-term disability, voluntary AD&D coverage, voluntary accident coverage, voluntary life insurance, voluntary disability insurance, and voluntary long-term care insurance.
• eligible employees can also receive mobile service & home internet discounts, pet insurance, and access to commuter and transit programs!

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Number of Employees: 5,001-10,000 employees