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Verizon seeks an Engr III Consultant - AI Science in Bengaluru to lead end-to-end AI services powering both traditional and generative use cases. You will design, deploy, and optimize AI/ML solutions across Python, cloud platforms, and modern frameworks, collaborating with cross-functional teams.
The role emphasizes scalable distributed systems, model serving, and performance analysis in GPU-accelerated environments, with hybrid work and 40 weekly hours.
You want more out of a career. A place to share your ideas freely — even if they’re daring or different. Where the true you can learn, grow, and thrive. At Verizon, we power and empower how people live, work and play by connecting them to what brings them joy. We do what we love — driving innovation, creativity, and impact in the world. Our V Team is a community of people who anticipate, lead, and believe that listening is where learning begins. In crisis and in celebration, we come together — lifting our communities and building trust in how we show up, everywhere & always. Want in? Join the #VTeamLife.
As Engr III Consultant - AI Science you will play a leading role in building, deploying and managing end to end AI Services to power traditional and generative AI use cases.
Must-Have: Design, develop, and implement innovative AI/ML solutions using Python, CI/CD, public cloud platforms, and JavaScript frameworks.
Must-Have: Contribute to developing robust and scalable distributed computing systems for large-scale data processing.
Must-Have: Implement and analyze the performance of advanced algorithms, including those from deep learning and generative AI.
Design and implement AI/ML pipelines for efficient model training and deployment.
Collaborate effectively with cross-functional teams to understand business needs and deliver impactful solutions.
Must have experience on Model-serving runtimes Like BentoML or TensorFlow Serving (TFX) or Triton Inference Server
Must have experience on Model-serving platforms like Cloud-provider platforms (Amazon SageMaker, Vertex AI, Azure Machine Learning) KServe , Ray .
Understanding of SOTA algorithms, especially in personalization, cognitive and generative models. Must have good understanding and ability to explain both the code and the underlying math used in algorithms/models.
Familiarity with multi modal data, vector and graph databases and data warehousing fundamentals
Experience with cloud platforms like GCP, AWS and their respective AI services
Must have Knowledge of GPU/CPU architecture and distributed computing
Understanding of containerization(Docker) orchestration (Kubernetes) and CI/CD pipelines
Exposure to large-scale AI training, understanding of the compute system concepts (latency/throughput bottlenecks, pipelining, multiprocessing etc) and related performance analysis and tuning
Qualifications:
Even better if you have :
In this hybrid role, you’ll have a defined work location that includes work from home and assigned office days set by your manager.
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Verizon is an equal opportunity employer. We evaluate qualified applicants without regard to race, gender, disability or any other legally protected characteristics.