AWS Architect

Machine Learning Technologies, LLC; Charlotte (NC); On-site; USD 89,000 - 126,000; Full time

Job summary

Machine Learning Technologies, LLC in Charlotte, NC is hiring an AWS Architect for a 12-month engagement. You will build MILP-based optimization models in Python and deploy scalable cloud workflows on AWS using Fargate, Lambda, Step Functions, and S3, with Terraform.

Responsibilities include ingesting predictive asset-health data, ensuring deterministic execution and explainability, and leveraging AI-assisted tooling to accelerate delivery.

Qualifications

• Proven experience building MILP models and optimization workflows.
• Strong Python programming skills with Pyomo or PuLP.
• Experience with commercial solvers (Gurobi/HiGHS/CBC).
• Cloud deployment skills on AWS and IaC with Terraform.

Responsibilities

• Mathematical Modeling: Formulate and tune MILP models in Python with Pyomo/PuLP and solvers (Gurobi/HiGHS/CBC).
• Cloud Architecture & Deployment: Build scalable cloud microservices on AWS (Batch on Fargate, Lambda, Step Functions, S3) using Terraform.
• Data Integration: Ingest asset-health outputs to feed optimization models.
• Deterministic Execution & Explainability: Create robust run harnesses with diagnostics and auditable outputs.
• AI-Assisted Engineering: Use GitHub Copilot, SDD, and AI agents to accelerate software delivery.

Skills

MILP modeling

Python programming

Pyomo

PuLP

Gurobi

HiGHS

CBC

Cloud architecture

Tools

AWS

Terraform

S3

Lambda

Fargate

Step Functions

Job description

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

Job Title: AWS Architect
Location: Charlotte, NC
Duration: 12 Months + Extension
Bill Rate: $78/hour
Job Type: W-2, 1099, C2C
Client: To Be Discussed Later
Work Authorization: US-Citizen, H-1B, OPT-EAD, GC-EAD

Job Description:

• Mathematical Modeling: Formulate and tune Mixed-Integer Linear Programming (MILP) models using Python frameworks (Pyomo, PuLP) and solvers (Gurobi, HiGHS, CBC) to handle budget, resource, and portfolio constraints.
• Cloud Architecture & Deployment: Package optimization workflows as scalable cloud microservices on AWS (AWS Batch on Fargate, Lambda, Step Functions, S3) using Terraform.
• Data Integration: Ingest predictive asset-health outputs (Probability of Failure, Remaining Useful Life) to feed optimization models.
• Deterministic Execution & Explainability: Build robust run harnesses for reproducible results, diagnostic tools (constraint relaxation/infeasibility analysis), and auditable outputs (shadow prices, binding constraints).
• AI-Assisted Engineering: Utilize GitHub Copilot, Spec-Driven Development (SDD), and AI agents to enhance software delivery and build scenario-explanation tools.

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.