Senior AI​/ML Architect

Job Duties and Responsibilities

Candidates must be willing to participate in at least one in-person interview, which may include a live whiteboarding or technical assessment session.

• 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

• Bachelor’s or Master’s degree in Electrical Engineering, Computer Science, or a related technical field
• 7+ years of experience in telecom architecture, network design, or solutions engineering
• Experience in writing and responding to technical RFPs/RFIs
• Hands‑on experience with network validation, lab PoCs, and troubleshooting

• 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

#LI-LM1

Compensation: $/Year – $/Year

We 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.

Candidates need to successfully complete a pre‑employment screen, which may include a drug test and DMV check. Our company is committed to fostering an inclusive and equitable workplace where every individual has the opportunity to succeed. We are dedicated to providing individuals with criminal or arrest records a fair chance of employment in accordance with local, state, and federal laws.

We pride ourselves on developing and promoting talent as an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status. Echo Star will accommodate sincerely held religious beliefs of employees if such accommodations are not undue hardships. All qualified applicants with arrest or conviction records will be considered for employment in accordance with local, state, and federal law.

You may redact any information that identifies age, date of birth, or dates of school/graduation from your application documents before submission and throughout our application process. Echo Star will provide reasonable accommodation to otherwise qualified job applicants and employees with known physical or mental disabilities, unless doing so poses an undue hardship on the Company.

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