Overview Join T-Mobile Advertising Solutions to build privacy first ML systems at scale. You will lead end to end ML/data product development, collaborate with cross functional teams, and shape solutions that impact advertisers and consumer privacy. The role blends machine learning, software engineering, and big data, with a Lean, build measure learn culture. You'll operate in cloud environments, driving experimentation and production readiness. This is an opportunity to shape AI capabilities in a privacy conscious ad tech platform.
Compensation / Benefits- medical, dental, and vision insurance
- 401(k) and employee stock grants
- employee stock purchase plan
- paid time off and holidays
- paid parental and family leave
- tuition assistance
Responsibilities- Lead end to end ML/data product development from problem framing to deployment and monitoring
- Build scalable data, training, and inference pipelines using distributed processing and cloud tech
- Apply statistical methods and experimentation to ensure quality and impact
- Write production quality code and advance engineering best practices (testing, CI/CD, observability)
- Collaborate cross functionally while guiding other engineers and data scientists
Key requirements- 4-7 years building/deploying ML and deep learning solutions at scale; familiarity with MLOps and DevOps
- 4-7 years experience with big data architectures and large scale data warehousing (e.g., BigQuery, Snowflake, Redshift)
- 4-7 years experience with large scale distributed data systems and cloud platforms (SQL, Python, Scala, AWS)
- 4-7 years solving complex data/ML challenges in production using modern engineering practices
- Advanced degree with 3+ years or Bachelor's with 5+ years in quantitative field
- Strong AI/ML foundation, statistical modeling, optimization, and design thinking
- Proficiency in cloud services (GCP, AWS) and Python/PySpark (pandas, scikit learn, scipy, numpy)
- collaboration
- leadership
- communication
- Python
- PySpark
- pandas
