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.
What you’ll be doing…
The work you'll be doing is on ML Engineering - mainly the Model Inferencing layer at the enterprise level. This will enhance the experience for Data Scientists and ML Engineers to build world-class solutions at scale.
As a Senior Engineer,
Working with stakeholders to understand requirements and effectively prioritize implementation.
Build, secure, scalable, and stable predictive, generative, and agentic AI solutions.
Driving the technical design and implementation of large-scale platforms, reusable AI products and business-ready context by utilizing modern and open-source technologies, in a hybrid cloud environment.
Lead or manage the deployment, and maintenance of AI platforms and frameworks at scale along with delivering core AI services across Generative & Agentic AI landscape
Building Non-Functional KPIs across Production deployments of AI apps and Agents across the Enterprise AI platform
Managing KPIs to measure the effectiveness, efficiency, and impact of AI solutions, ensuring alignment with business objectives.
Ensuring best practices in AI development, including model validation, testing, and deployment, while adhering to regulatory and ethical standards.
What we're looking for…
You will be Responsible for implementing and performance-tuning the fine-tuning and inferencing layer of Agents. You are a good team player and having go-getter kind of attitude with good inter-personal skills. You will Lead and provide guidance to team with regards to Plan, Configure, Deploy and Operate in cloud solutions.
You'll need to have:
Bachelor’s degree or four or more years of work experience.
Four or more years of relevant work experience.
Three or more years of experience in cloud native AI services.
Three or more years of experience in developing scalable AI Agents.
Three or more years of experience with build and deployment tools: ArgoCD,Cloud Build
Primary Skills: Python, Fast API, Agent Development Frameworks (Langgraph, Google ADK,Claude SDK), Container native scaling practices.
Mathematical & Theory: Linear Algebra: Matrices, eigenvalues, eigenvectors, and vector operations. Calculus: Derivatives, partial derivatives, chain rule (essential for backpropagation), and gradients. Probability & Statistics: Hypothesis testing, Bayesian probability, mean, variance, and probability distributions. Machine Learning Fundamentals: Bias-variance tradeoff, regression, classification, clustering, and decision trees. Deep Learning: Neural networks, CNNs, RNNs, and Transformers.
Programming & Software Engineering: Languages: Python is the industry standard, supported by C/C++ or Rust for performance-critical ML components, and SQL for database querying. Machine Learning Libraries: PyTorch (widely preferred in industry), TensorFlow/Keras, and Scikit-learn. Software Engineering Principles: Clean code, Object-Oriented Programming (OOP), version control (Git), and REST API building (FastAPI, Flask).
MLOps, Data, & Infrastructure: Data Pipelines: Experience with data extraction, transformation, and loading (ETL), alongside data manipulation libraries like Pandas, NumPy, or PySpark. Model Deployment: Containerization (Docker), and orchestration tools (Kubeflow, Apache Airflow). Cloud Services: Hands-on experience with cloud infrastructure, such as Amazon Web Services (AWS), Google Cloud Platform (GCP)
Even better if you have one or more of the following:
A Master’s is highly advantageous and expected for research-heavy roles or top AI/ML startups.
Experience working on Any model inferencing layer
Good to have Knowledge on PCF/Docker/Kubernete
Experience of working in agile environment and good understanding of Agile processes Having experience working in Cloud environment would be added advantage, mainly GCP
Secondary Skills Docker Kubernetes
Verizon is an equal opportunity employer. We evaluate qualified applicants without regard to race, gender, disability or any other legally protected characteristics.
Want to know if this job is worth applying to?
Sydney, New South Wales, Australia
Onsite