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.
Bachelor's, Masters or PhD in Computer Science, Information Technology, Engineering, or related field.
3+ years of in productionization of ML/AL
3+ years' experience with deployment tools (Kubernetes and Docker is preferred)
3+ 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)
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
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
How you'll grow
At Deloitte, our professional development plan focuses on helping people at every level of their career to identify and use their strengths to do their best work every day. From entry-level employees to senior leaders, we believe there's always room to learn. We offer opportunities to help sharpen skills in addition to hands-on experience in the global, fast-changing business world. From on-the-job learning experiences to formal development programs at Deloitte University, our professionals have a variety of opportunities to continue to grow throughout their career. Explore Deloitte University, The Leadership Center .
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* The salary listed in the header is an estimate based on salary data for similar jobs in the same area. Salary or compensation data found in the job description is accurate.