Senior AIML Architect
Listed on 2025-11-28
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IT/Tech
AI Engineer, Machine Learning/ ML Engineer
Company Summary
Echo Star is reimagining the future of connectivity. Our business reach spans satellite television service, live-streaming and on-demand programming, smart home installation services, mobile plans and products. Today, our brands include Boost Mobile, DISH TV, Gen Mobile, Hughes and Sling TV.
Department SummaryOur Wireless Technology team is pioneering the future of connectivity. We’re developing and enhancing a unique hybrid network model—combining our advanced, cloud-native 5G core with the nationwide reach of our partners. This approach ensures our network is flexible and powerful, designed to satisfy the social, economic, and transformative needs of the changing world.
Job Duties and ResponsibilitiesWe are seeking a visionary Senior AIML Architect to define and deliver AI-driven solutions that optimize network performance, elevate customer experience, and streamline operations for Boost Wireless. You will own the end‑to‑end AI architecture—from strategy through deployment—by designing scalable ML models, real‑time analytics frameworks, and intelligent automation pipelines across our enterprise and cloud-native environments. As a key collaborator, you’ll partner with network engineers, data scientists, and business stakeholders to translate requirements into robust AI services that deliver measurable business impact.
Key Responsibilities- Lead the development and implementation of an enterprise AI architecture strategy aligned with digital transformation objectives
- Design, train, and deploy ML models for network optimization (traffic prediction, anomaly detection, self‑healing) and operational analytics (predictive maintenance, fraud detection)
- Build real‑time data processing frameworks to support high‑volume streaming analytics for network and customer insights
- Integrate AI/ML services into OSS/BSS platforms, ensuring smooth interoperability and automated decision‑making
- Architect AI solutions for enterprise network slices, leveraging edge computing and cloud‑native principles to drive performance and scalability
- Establish governance and best practices for model lifecycle management, version control, explainability, and compliance with AI ethics guidelines
- Mentor and guide junior AI/ML engineers, fostering a culture of experimentation, continuous learning, and cross‑functional collaboration
Education and Experience:
- Master’s or Ph.D. in Computer Science, AI/ML, or a related technical discipline
- 10+ years of AI/ML development experience, including at least 5 years in telecom or mobile network environments
Skills and
Qualifications:
- Deep expertise in enterprise architectures and edge/cloud‑native deployments
- Proficiency with AI/ML platforms (IBM Watson, AWS Bedrock, Data Bricks, Google Vertex) and libraries (Tensor Flow, PyTorch, Scikit‑learn) and big data tools (Kafka, Spark, Hadoop)
- Strong understanding of network protocols, OSS/BSS systems, and real‑time analytics
- Demonstrated leadership in architecting and delivering large‑scale AI programs
- Excellent stakeholder management, verbal/written communication, and cross‑team collaboration skills
- Hands‑on experience with AI‑powered network tuning, network slicing, and intent‑based networking preferred
- Familiarity with advanced AI techniques—deep reinforcement learning, federated learning, and model explainability preferred
- Knowledge of AI ethics, regulatory compliance in telecom, and data privacy frameworks preferred
Candidates must be willing to participate in at least one in‑person interview, which may include a live whiteboarding or technical assessment session.
Salary RangesCompensation: $127,050 /Year - $181,500 /Year
BenefitsWe offer versatile health perks, including flexible spending accounts, HSA, a 401(k) Plan with company match, ESPP, career opportunities, and a flexible time away plan. All benefits can be viewed here: DISH Benefits.
The base pay range shown is a guideline. Individual total compensation will vary based on factors such as qualifications, skill level, and competencies; compensation is based on the role’s location and is subject to change based on work location.
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