Full-Time

AI/ML Cloud Consultant

Vertical Relevance

Vertical Relevance

No salary listed

No H1B Sponsorship

Short Hills, Millburn, NJ, USA

Hybrid

The role may be performed remotely or from the New York or New Jersey office.

PhD

Category
AI & Machine Learning (1)
Required Skills
Python
TensorFlow
R
Keras
PyTorch
Apache Spark
Machine Learning
CloudFormation
AWS
Hadoop
Data Analysis
Reinforcement Learning
Requirements
  • Hands-on experience building and implementing machine-learning or artificial-intelligence models in Amazon Web Services.
  • Experience in software or technology customer-facing work.
  • A Doctor of Philosophy in Computer Science, Statistics, Machine Learning, Data Science, Electrical Engineering, or a related field.
  • Legal authorization to work in the United States without requiring employer sponsorship now or in the future.
  • Proficiency in Python and R.
  • Experience with Hadoop, TensorFlow, Spark, Keras, MxNet, PyTorch, and Jupyter Notebooks.
  • Knowledge of recurrent neural networks, reinforcement learning, and transformers.
  • Experience with Amazon Web Services infrastructure scripting, storage, compute, networking, analytics, security, identity, compliance, application integration, and machine-learning services, including CloudFormation, S3, Lambda, VPC, Glue, EMR, IAM, Step Functions, SageMaker, Deep Learning AMI, and Deep Learning Container.
Responsibilities
  • Enable customers to solve complex data-science problems, including problem framing, data preparation, scripting, model building, model deployment, model management, and output consumption.
  • Consult, plan, design, and implement machine-learning and artificial-intelligence solutions using Amazon Web Services machine-learning services.
  • Deliver machine-learning projects end to end by understanding business needs, aggregating and exploring data, building and validating predictive models, and deploying completed models with concept-drift monitoring and retraining.
  • Use Amazon Web Services artificial-intelligence services, machine-learning platforms, and frameworks to help customers build machine-learning models.
  • Work with Big Data, Internet of Things, and high-performance computing consultants to analyze, extract, normalize, and label relevant data, and work with engineers to operationalize customer models after prototyping.
  • Develop technical content such as automation tools, reference architectures, and white papers.
  • Provide customer-focused innovation and translate ideas into measurable results.
  • Convey customer needs and feedback to inform technology roadmaps, document implementation challenges, and recommend expanded or new capabilities.
  • Assist with technical briefs documenting solutions and with reference-architecture implementations.
  • Work with Marketing and Alliances to write blog posts and develop internal case studies.

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Founded

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