1 day ago
Chicago, IL, USA +9 moreMid Level
H1B sponsor
Base Salary
$131k - $195k/yr
Responsibilities
- Implement end-to-end AI/ML and GenAI projects, including business discovery, data preparation, model development, deployment, and monitoring.
- Design and implement high-performance, reliable, scalable, and secure machine learning pipelines.
- Design scalable ML solutions and MLOps operations using AWS services and GenAI technologies where appropriate.
- Collaborate with Applied Science, DevOps, Data Engineering, Cloud Infrastructure, and Applications teams to operationalize data and AI/ML models.
- Advise customers on AI/ML, GenAI solutions, cloud architectures, industry trends, and migration strategies.
- Lead implementation processes, optimize performance, manage risks, and ensure adherence to best practices and industry standards.
- Share knowledge through mentoring, training, publications, and reusable technical artifacts.
Requirements
- At least 3 years of customer-facing experience engaging executives, technologists, or partners to solve business problems with advanced technologies.
- At least 3 years of experience building machine learning and generative AI models for business applications.
- Experience with cloud machine learning services such as Amazon SageMaker and generative AI applications.
- At least 3 years of experience with coding, data querying languages such as SQL, and scripting languages such as Python.
- Preferred knowledge of AWS compute, storage, networking, security, database, machine learning, and serverless services.
- Preferred experience with SageMaker, Bedrock, EC2, ECS, EKS, OpenSearch, and AWS certifications.
- Preferred 2+ years of experience designing, deploying, and evaluating AI agents and orchestration approaches, including frameworks such as LangChain, LangGraph, or LlamaIndex.
- Preferred 3+ years of experience with deep learning, computer vision, human-robot interaction, or algorithm implementation using PyTorch or TensorFlow.
- Preferred experience building ML pipelines with data preprocessing, distributed and GPU training, model deployment, monitoring, retraining, container, and CI/CD practices.
- Preferred healthcare and life sciences domain expertise.
Benefits
- Comprehensive health insurance, including medical, dental, vision, prescription, Basic Life and AD&D insurance, and optional supplemental life plans.
- Employee assistance, mental health support, medical advice line, flexible spending accounts, and adoption and surrogacy reimbursement coverage.
- 401(k) matching, paid time off, and parental leave.
- Mentorship, knowledge-sharing, learning experiences, and career-advancement resources.
- Flexible work-life culture; the customer-facing role may involve travel to customer sites as needed.
About Amazon
Amazon builds and operates a global e-commerce marketplace, logistics network, and consumer devices, and provides cloud computing via AWS for businesses and developers. The company earns revenue from online retail, third‑party seller services, subscriptions like Prime, advertising, and AWS usage. Founded in 1994 and headquartered in Seattle, it is publicly traded on NASDAQ (AMZN) and serves customers in dozens of countries.