Delivery Consultant, Ai/ml, Aws Professional Services, Healthcare & Life Sciences

Amazon Amazon · Big Tech · IN, KA, Bengaluru · Solutions Architect

Machine Learning Engineer within AWS Professional Services focused on designing, implementing, and scaling AI/ML and Generative AI solutions for healthcare and life sciences customers. Responsibilities include understanding customer needs, data aggregation, model building, validation, deployment, and operationalization, with a focus on delivering business impact and customer success.

What you'd actually do

  1. Understand the customer’s business need and guide them to a solution using our AWS AI Services, AWS AI Platforms, AWS AI Frameworks, and AWS AI EC2 Instances .
  2. Assist customers by being able to deliver a AI/Ml and GenAI project from beginning to end, including understanding the business need, aggregating data, exploring data, building & validating predictive models, and deploying completed models to deliver business impact to the organization.
  3. Use Deep Learning frameworks like MXNet, Caffe 2, Tensorflow, Theano, CNTK, and Keras to help our customers build DL models.
  4. Use SparkML and Amazon Machine Learning (AML) to help our customers build ML models.
  5. Use Amazon Bedrock and various GenAI Tools to help customers build GenAI Applications.

Skills

Required

  • Machine Learning
  • Generative AI
  • Deep Learning frameworks (MXNet, Caffe 2, Tensorflow, Theano, CNTK, Keras)
  • SparkML
  • Amazon Machine Learning (AML)
  • Amazon Bedrock
  • GenAI Tools
  • Data analysis
  • Model validation
  • Model deployment
  • Model operationalization
  • Model retraining
  • Customer engagement

Nice to have

  • AWS AI Services
  • AWS AI Platforms
  • AWS AI Frameworks
  • AWS AI EC2 Instances
  • Big Data consulting
  • DevOps consulting

What the JD emphasized

  • customer facing
  • design, evangelize, implement, and scale AI/ML solutions
  • Generative AI algorithms
  • deep expertise in machine learning, generative AI
  • architecting complex, scalable, and secure machine learning solutions
  • develop proof-of-concepts
  • implementing AI and generative AI solutions at scale
  • design and run experiments
  • research new algorithms
  • optimize risk, profitability, and customer experience
  • deliver a AI/Ml and GenAI project from beginning to end
  • building & validating predictive models
  • deploying completed models to deliver business impact
  • operationalize models
  • identifying model drift and retraining models

Other signals

  • customer facing
  • design, evangelize, implement, and scale AI/ML solutions
  • Generative AI algorithms
  • deep expertise in machine learning, generative AI
  • architecting complex, scalable, and secure machine learning solutions
  • develop proof-of-concepts
  • implementing AI and generative AI solutions at scale
  • design and run experiments
  • research new algorithms
  • optimize risk, profitability, and customer experience
  • deliver a AI/Ml and GenAI project from beginning to end
  • building & validating predictive models
  • deploying completed models to deliver business impact
  • operationalize models
  • identifying model drift and retraining models