Engr III Spec-AI/ML Engring

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What you'll be doing:

The AI Science team is seeking a Senior AI Scientist/Engineer to bridge the gap between cutting-edge Machine Learning research and high-scale production systems. In this role, you will collaborate closely with Data Engineers and Platform Engineers to design, train, optimize, and deploy advanced ML models and AI infrastructure. You will take ownership of turning complex algorithmic innovations into robust, scalable, and low-latency production applications.
Key Responsibilities

• Model Productionization & Scaling: Architect, implement, and maintain scalable infrastructure to train, fine-tune, and deploy state-of-the-art AI models (e.g., Large Language Models, Multimodal Models, Deep Learning architectures).

• Research & Development Collaboration: Work alongside Research Scientists to translate novel theoretical concepts and prototypes into clean, modular, and performant codebases.

• Inference & Training Optimization: Optimize model inference and training workflows for memory, speed, and cost efficiency using techniques like quantization, pruning, distillation, and distributed execution.

• ML Pipelines & Data Architecture: Design resilient data pipelines, dataset curation workflows, and automated evaluation suites to ensure continuous model improvement and regression testing.

• System Design & MLOps: Build robust monitoring, logging, and continuous deployment (CI/CD for ML) systems to track model performance, drift, and system health in production.

• Technical Leadership: Code-review team contributions, mentor junior engineers, and drive technical best practices for engineering rigor within the AI Science organization.t

What we’re looking for...

You'll need to have

• Bachelor’s or degree in Computer Science, Artificial Intelligence, Data Science, or a related quantitative field or four or more years of work experience.

• Three or more years focused on building, deploying, and maintaining ML/AI models in production.

• Expert-level programming proficiency in Python and deep understanding of modern ML frameworks (PyTorch, TensorFlow, or JAX).

• Strong background in system design, object-oriented programming, data structures, and software engineering best practices.

• Experience with distributed model training and inference systems (e.g., Ray, DeepSpeed, vLLM, Megatron-LM).

• Experience with cloud environments (AWS, GCP, or Azure), containerization (Docker, Kubernetes), and modern MLOps tool chains.

Even better if you have one or more of the following:

• Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related quantitative field.

If Verizon and this role sound like a fit for you, we encourage you to apply even if you don’t meet every “even better” qualification listed above.

Verizon is an equal opportunity employer. We evaluate qualified applicants without regard to race, gender, disability or any other legally protected characteristics.