Interested in this AI/ML Engineer role at T-Mobile?
Apply Now →About This Role
At T\-Mobile, we invest in YOU! Our Total Rewards Package ensures that employees get the same big love we give our customers. All team members receive a competitive base salary and compensation package \- this is Total Rewards. 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. That’s how we’re UNSTOPPABLE for our employees!
This is NOT a remote position. T\-Mobile is a hybrid work environment requiring the successful candidate be in the office three (3\) days per week. This position is open to candidates in Bellevue, WA and Frisco, TX only.
Job Overview
The Principal AI Technical Product \& Strategy Manager is a visionary product leader, customer evangelist, and execution driver responsible for bringing T\-Mobile's most ambitious AI innovations from concept to commercial success. This role owns end\-to\-end product strategy and delivery for breakthrough AI initiatives, working in a fast\-paced, entrepreneurial environment within T\-Mobile's AI Commercialization team. This roles combines customer understanding, strategic thinking, and hands\-on execution to deliver AI products that create new revenue streams and differentiated customer experiences. This role requires a unique blend of startup agility and enterprise scale capabilities, working closely with cross\-functional teams to validate, build, and launch AI\-powered solutions that push the boundaries of what's possible in telecommunications.
Day to day activities or responsibilities include: conducting market research; writing features or user stories; determining specifications; defining long\-term strategy of the product; creating the product road map; driving technical delivery end to end; defining scope for releases/product increments; partnering with development, project/program management, marketing, and other key stakeholders to define release schedule; and support/drive go\-to\-market activities as needed.Job Responsibilities:
Vision \& Strategy for AI Products
- Owns product vision, strategy, and roadmap for flagship AI initiatives from concept to market launch
- Conducts deep customer research and market analysis to identify breakthrough AI opportunities
- Develops compelling business cases and value propositions for new AI products
- Partners with leadership to secure funding and resources for innovation initiatives
- Defines success metrics and tracks progress against ambitious growth targets
- Anticipates AI trends and competitive threats, incorporating insights into product strategy
- Designs and drives end user product research.
- Conducts analysis of quantitative and qualitative data to identify product innovation opportunities or root cause of issues, and assess opportunity size and impact. May work with data scientists to answer complex questions or identify meaningful insights from data.
- Leverages rapid hypothesis driven testing methodologies and experiments (i.e. paper prototype, A/B testing, etc.) to inform direction, prioritize investment.
- Conducts cost\-benefit / ROI / NPV analysis, to support decision making.
- Works with stakeholders and follows enterprise process to secure and maintain product funding.
- Anticipates industry trends, direction, innovation, analyses potential impacts or opportunities to customer / product, and incorporates analyses into product process.
- Communicates, influences, and sells ideas at SVP/EVP/C\-Level and below. This includes regularly delivering product presentations.
- Drives specific ad hoc analysis and presents information to SVP/EVP/C level and below on request.
- Owns product feature set or technical improvements to improve customer experience.
- Leads discussions with external third parties to assess partnerships and licensing opportunities.
Customer Evangelist
- Leads customer discovery and validation activities for new AI products
- Writes detailed product requirements, user stories, and acceptance criteria for AI\-powered features
- Designs and executes rapid prototyping and MVP development cycles
- Conducts user testing and iteration based on customer feedback
- Ensures AI products deliver measurable customer value and exceptional user experience
- Advocates for customer needs throughout the development process
- Leverages customer insights for product vision, strategy, roadmap, priorities.
- Create, manage, foster an active VOC feed for themselves and team.
- Actively looks for opportunities to delight or meet customer’s unmet needs.
- Evangelizes and advocates for the customer both internally (IC through C level) and externally, perpeuating the customer\-first mindset.
- Creates an environment and culture where the team is immersed in customer\-first mindset.
- Tests ideas with real customers to ensure that the product deliver the desired benefit.
Product Execution \& Technical Delivery
- Collaborates with Technical Architects to ensure AI solutions are technically feasible and scalable
- Partners with UX/UI designers to create intuitive and engaging AI interactions
- Works with engineering teams (both internal and matrixed) to deliver products on time and within scope
- Coordinates with GTM and commercialization teams to develop launch strategies
- Drives resolution of technical and business challenges that arise during development
- Translates product/platform strategy by writing detailed features and user stories consumable for Dev teams for the highest level complexity products with multiple transactions and touchpoints across many teams. This work may include creation of prototypes.
- Collaborates with PM and Dev leaders to design, architect and assemble effective Agile delivery teams in the Agile Release Train and Agile Teams.
- Scopes and ensures alignment on the prioritization of activities based on business and customer impact.
- Collaborates with Architecture and Dev teams to ensure technical debt and long term technical investment is factored into roadmap.
- Ensures existing production defects are factored into regular backlog prioritization for resolution based on priority
- In scaled teams, holds regular meetings and coordination activities with other PM’s and Product Owners (if applicable) to ensure parallel work is in sync and dependencies are known.
- Generates and maintains dashboards and reports that track product health and success metrics, technical KPI’s.
- Runs beta and pilot programs with early\-stage products and samples.
- Collaborates with advertising and public relations to promote product.
- Supports sales, marketing, and other stakeholder teams with product or technical knowledge and additional documentation.
- Assists with the overall execution relating to all aspects of the software development process, from defining the strategy and architecture through deployment and support.
- Anticipates and communinctes technical challenges to stakeholders and makes educated trade\-off decisions with the team.
- Accountable for product quality and performance in production environment. Accountable for product and Dev team response in event of critical or high impacting defect , including communications to stakeholders at all levels.
- Manages development of adoption tools and training materials. Identify execution, operational, organizational issues that impede product success. Drive improvement plan to change or resolve issues (within sphere of influence).
- Support and enable core agile practices and tenants: efficient just\-in\-time flow; lean practices; elimination of waste; DevOps CICD
Relationship \& People, Professional Development
- Builds strong relationships with Product, IT, and Data \& AI organizations
- Negotiates priorities and resources across multiple stakeholder groups
- Communicates product roadmaps and launches to internal and external audiences
- Mentors junior product managers and shares innovation best practices
- Represents T\-Mobile at industry events and innovation forums
- Collaborates and develops positive working relationships with many technical and non\-technical teams, including sales, commercial accounting, marketing, legal, go\-to\-market, finance, Dev, Architecture, Engineering. Works with outside partners and other third parties.
- Also responsible for other Duties/Projects as assigned by business management as needed.
REQUIRED QUALIFICATIONS:
Education:
- Bachelor's Degree in Computer Science, Engineering, IT or equivalent experience.
Experience:
- 8\+ years’ experience in hands on technical role writing production code, solution engineering, or technical archtecture in large scale company / appplication / product environment.
- More than 10 years Relevant Product Management experience in an agile software product development environment.
Required Knowledge, Skills, and Abilities
- Business Operations \- Demonstrates complete mastery of business side skills (communication, customer research, product vision, feature definition), as well as technical architecture, Dev, and execution skills.
- Business Analysis \- Validated analytical skills with demonstrated ability to identify/analyze/synthesize product use data and use the data to drive decisions.
- Customer Experience Management \- Mastery level (industry leading) understanding of customer experience.
- Technology
- Mastery level understanding of platform technologies and components such as security, performance, optimization, API integration.
- Expert level knowledge of full technology stack on which your assigned product runs.
- Agile Methodologies \- Shown success in directing matrixed resources and delivering software, with Agile Scrum methodologies and other commonly used tools, across multiple teams.
- Partnership Development \- Experience working with external partners, vendors, and ecosystem players
- Innovation Methodology \- Expertise in design thinking, lean startup methodologies, rapid prototyping, and hypothesis\-driven development
- Collaboration \- Experience with successive elaboration and ability to develop Initiatives, Features and User Stories that the DevOps teams can ingest.
- Product Management \- Experience delivering large and complex business/technology initiatives as Product Manager or lead technology role.
- Communication \- Shown ability to effectively and efficiently communicate with Leadership, technical and non\-technical audiences while employing a high degree of collaboration and influence.
- Integration \- Knowledge and experience with integration patterns, API’s, and protocols such as REST, EDI, SOAP, etc.
- AI/ML Product Expertise \- Deep understanding of AI technologies, capabilities, and limitations. Experience with LLMs, conversational AI, and ML platforms
- Data\-Driven Decision Making \- Proficiency with analytics tools and metrics\-based product optimization
\#LI\-Corporate
- At least 18 years of age
- Legally authorized to work in the United States
Travel:
Travel Required (Yes/No):
DOT Regulated:
DOT Regulated Position (Yes/No): No
Safety Sensitive Position (Yes/No): No
Base Pay Range: $139,700 \- $252,000
Corporate Bonus Target: 20%
The pay range above is the general base pay range for a successful candidate in the role. The successful candidate’s actual pay will be based on various factors, such as work location, qualifications, and experience, so the actual starting pay will vary within this range.
At T\-Mobile, 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. Certain positions in Customer Care are eligible for monthly bonuses based on individual and/or team performance. To find the pay range for this role based on hiring location, click here.
At T\-Mobile, our benefits exemplify the spirit of One Team, Together! A big part of how we care for one another is working to ensure our benefits evolve to meet the needs of our team members. Full and part\-time employees have access to the same benefits when eligible. We cover all of the bases, offering 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. We don't stop there \- eligible employees can also receive mobile service \& home internet discounts, pet insurance, and access to commuter and transit programs! To learn about T\-Mobile’s amazing benefits, check out *www.t\-mobilebenefits.com**.*
Never stop growing!
As part of the T\-Mobile team, you know the Un\-carrier doesn’t have a corporate ladder–it’s more like a jungle gym of possibilities! We love helping our employees grow in their careers, because it’s that shared drive to aim high that drives our business and our culture forward. By applying for this career opportunity, you’re living our values while investing in your career growth–and we applaud it. You’re unstoppable!
T\-Mobile USA, Inc. is an Equal Opportunity Employer. All decisions concerning the employment relationship will be made without regard to age, race, ethnicity, color, religion, creed, sex, sexual orientation, gender identity or expression, national origin, religious affiliation, marital status, citizenship status, veteran status, the presence of any physical or mental disability, or any other status or characteristic protected by federal, state, or local law. Discrimination, retaliation or harassment based upon any of these factors is wholly inconsistent with how we do business and will not be tolerated.
Talent comes in all forms at the Un\-carrier. If you are an individual with a disability and need reasonable accommodation at any point in the application or interview process, please let us know by emailing ApplicantAccommodation@t\-mobile.com or calling 1\-844\-873\-9500\. Please note, this contact channel is not a means to apply for or inquire about a position and we are unable to respond to non\-accommodation related requests.
Salary Context
This $139K-$252K range is above the median for AI/ML Engineer roles in our dataset (median: $175K across 2162 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At T-Mobile, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills in Demand for This Role
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $214,900 based on 6,420 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($195K) sits 9% below the category median. Disclosed range: $139K to $252K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
T-Mobile AI Hiring
T-Mobile has 9 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Frisco, TX, US, Overland Park, KS, US, Bellevue, WA, US. Compensation range: $146K - $328K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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