AI

Deloitte in Los Angeles, CA

  • Type: Full Time
position filled

Position summary

The team Our Cloud Engineering team focuses on enabling our client’s end-to-end journey from On-Premise to Cloud, with opportunities in the areas of: Cloud Strategy, at scale AI/ML Productionization, Op Model Transformation, Cloud Development, Cloud Integration & APIs, Cloud Migration, Cloud Infrastructure & Engineering, and Cloud Managed Services. We help our clients see the transformational capabilities of Cloud as an opportunity for business enablement and competitive advantage.

Cloud Engineering supports our clients as they improve agility and resilience and identifies opportunities to reduce IT operations spend through automation by enabling Cloud. We accelerate our clients towards a technology-driven future, leveraging vendor solutions and Deloitte-developed software products, tools, and accelerators.
Work you’ll do

Exciting opportunity! We are looking for talented AI/ML Cloud Deployment Engineers to help drive high priority customer initiatives around AI/ML models at scale. You will help clients with design, deployment and optimization of production AI/ML environments. The role of the AI/ML Deployment Engineer is to create Machine Learning platform capabilities and solutions to integrate AI/ML model driven decision-making insights into everyday business processes of large enterprises. This unique role will involve a mix of automation, DevOps, and infrastructure engineering.
Qualifications Required
  • Bachelor’s, Masters or PhD in Computer Science, Information Technology, Engineering, or related field.
  • 10+ years of in productionization of ML/AL
  • 10+ years’ experience with deployment tools (Kubernetes and Docker is preferred)
  • 10+ years’ experience with cloud architecture including AWS, GCP and Azure and development methods

  • Proficiency in programing languages such as Python, Java, Scala

  • Proficiency in TensorFlow Serving

  • Understanding of model registries, feature stores, model versioning

  • Understanding of integrating ML/AI insights into front-end applications

  • Experience developing custom data models

  • Hands on experience in ML and deep learning platforms (e.g., TensorFlow, PyTorch, Keras, Caffe, etc.) and Deep Learning models (e.g., DNN, CNN, RNN and GAN)

  • Preferred Qualifications

  • Knowledge of machine learning, information retrieval, analytics, statistics, deep learning techniques
  • Strong background in various persistent storage models in Cloud
  • Experience in microservice architecture and developing AI-driven microservices for application consumption
  • Strong JavaScript/Mobile app development background. Development experience in “Single Page Apps” and “Progressive Apps” using Angular/React/Vue.
  • Proven track record managing large tech teams that desined and launched complex AI solutions
  • Experience in API development (GraphQL, Rest APIs)
  • Expertise in Jupyter as well as good exposure to data munging

  • Expertise in Spark for large scale data munging is a plus


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