Senior AIML Architect

Echostar Corporation•Littleton, CO

69d

About The Position

We 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 endâtoâend AI architecture-from strategy through deployment-by designing scalable ML models, realâtime 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.

Requirements

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
Deep expertise in enterprise architectures and edge/cloudânative deployments
Proficiency with AI/ML platforms (IBM - Watson, AWS - Bedrock, DataBricks, Google Vertex) and libraries (TensorFlow, PyTorch, Scikitâlearn) and big data tools (Kafka, Spark, Hadoop)
Strong understanding of network protocols, OSS/BSS systems, and realâtime analytics
Demonstrated leadership in architecting and delivering largeâscale AI programs
Excellent stakeholder management, verbal/written communication, and crossâteam collaboration skills

Nice To Haves

Handsâon experience with AIâpowered network tuning, network slicing, and intentâbased networking
Familiarity with advanced AI techniques-deep reinforcement learning, federated learning, and model explainability
Knowledge of AI ethics, regulatory compliance in telecom, and data privacy frameworks

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, selfâhealing) and operational analytics (predictive maintenance, fraud detection)
Build realâtime data processing frameworks to support highâvolume streaming analytics for network and customer insights
Integrate AI/ML services into OSS/BSS platforms, ensuring smooth interoperability and automated decisionâmaking
Architect AI solutions for enterprise network slices, leveraging edge computing and cloudânative 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 crossâfunctional collaboration