Senior AI/ML Engineer - AI Live Operations

Description

You will join the AI Live Operations team as a senior AI/ML engineer and work as a key individual contributor. The role focuses on keeping deployed AI models stable, safe and efficient once they meet real-world data and production traffic.

The company is several years into a plan to industrialize its data science and AI work, so AI will drive decisions and business processes across the company. With annual revenue above $130 billion and a lead in nationwide 5G, the company is moving from millions of automated predictions to trillions of real-time inferences, and you will help build and scale production AI systems in telecom.

The team is looking for someone who values precision, resilient systems and clean, scalable code, works well without close supervision, mentors junior engineers and shares technical knowledge across engineering.

Responsibilities

• Build and run real-time monitoring and observability pipelines that track throughput, latency and token costs for large language models.
• Watch production models for data drift and degradation, and keep prediction accuracy high over time.
• Set up automated continuous evaluation loops that gather user feedback and ground-truth telemetry to measure performance as it changes.
• Deploy real-time safety filters, guardrails and input and output moderation to reduce hallucinations and block inappropriate generated content.
• Build fallback paths that send failed requests to rule-based software or human queues so end users keep a good experience.
• Create automated CI/CD pipelines that retrain, validate and release updated models with no downtime.
• Act as the senior escalation point for production model incidents, diagnose live model problems, and ship urgent hotfixes or prompt changes.
• Work with platform architects and core data science teams to scale backend architectures across cloud, on-premises and edge network infrastructure.
• Partner with engineering and development teams on technical alignment, code reviews, and promoting secure and ethical AI practices.

Requirements

• A bachelor's degree, or at least four years of work experience.
• Four or more years of relevant experience, which can come from a mix of work, military service or specialized training.
• Even better if you have one or more of the following:
• A master's degree in computer science, data science, electrical engineering, mathematics or another highly technical field.
• Substantial hands-on experience deploying, monitoring and debugging complex machine learning or deep learning models at large production scale.
• Working knowledge of MLOps frameworks and automated pipeline tools such as Airflow, Kubeflow or MLflow.
• Advanced programming skills in Python, Java or C++, with a solid grasp of data structures and of cloud platforms such as AWS, Google Cloud or Azure.
• Extensive experience building safety guardrail middleware, monitoring dashboards and telemetry systems for Generative AI applications.
• Knowledge of distributed compute, database design and real-time streaming technologies such as Kafka or Spark.
• The company encourages you to apply even if you do not meet every 'even better' qualification above.

Conditions

Hybrid role with a defined work location that includes working from home and at least three days per week in the office, with the schedule set by your manager.

You are responsible for following the hybrid work policies.

Scheduled work is 40 hours per week.

The full-time annual salary range for the listed location(s) is $111,500.00 to $194,000.00.

Pay depends on your location and on the job-related skills and experience you confirm. The role is incentive based, so earnings can go higher.

Part-time pay is adjusted to match your hours.

Benefits

• Health and wellness options include medical, dental and vision coverage, short and long term disability, basic and supplemental life insurance, AD&D insurance, identity theft protection, pet insurance, and group home and auto insurance.
• A matched 401(k) savings plan.
• Up to 8 company-paid holidays and up to 6 personal days per year.
• Paid parental leave, adoption assistance, tuition assistance and other incentives.
• Premium pay may be available depending on the role, such as overtime, shift differential, holiday pay and allowances.
• Newly hired employees start with up to 15 days of vacation per year, which increases with service.
• Part-time employees may qualify for some of these benefits depending on their individual circumstances, and coverage varies.