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# Machine Learning Developer

- **Company:** BINGHAMTOM UNIVERSITY
- **Location:** United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Search Technologies, Autodesk Autocad
- **Published:** July 11, 2026
- **Apply:** https://www.themuse.com/jobs/autodesk/senior-machine-learning-developer-de5b54?utm_source=uconnect

## About the Role

* Bachelor's or Master's in CS/Engineering/Data Science or equivalent experience.
 * 5+ years combining software development and AI/ML for production systems.
 * Experience with ML libraries such as scikit-learn, PyTorch, Ray.
 * Experience building with APIs, services, containers, CI/CD.
 * Familiarity with time-series/sensor/simulation data and basic cloud platform services
 * Good teamwork, independent learning, * Data modeling, optimization, RL, numerical simulation
 * Practical LLM-application experience, vector search, RAG, MCP
 * Development of multi-tenant SaaS ML systems
 * AEC or civil industry experience or background

## Description

We build AI-driven software that helps water and AEC customers make operational decisions, plan and design - via modelling, optimizing, forecasting, simulation, and automation. You'll work on production ML systems and backend services that integrate with product data via modern APIs and Model Context Protocol MCP tooling. The role blends machine learning data science, LLM agentic workflows and code generation, and software engineering to deliver reliable, scalable functionality to our customers. Candidates are expected to keep current with modern applied AI techniques., * Implement, integrate, and optimize ML systems for forecasting, anomaly detection, simulation surrogates, and decision support.

 * Build production inference pipelines, APIs, and services
 * Design LLM applications (RAG, tool-calling, contextual Q&A) and agentic workflows that orchestrate multi-step tasks - including agentic code generation to automate model-driven actions.
 * Implement MCP routes, schemas, and integrations to connect models with structured product data and tools.
 * Ensure reliability with CI/CD, unit/integration/performance testing, observability, and monitoring (model drift, metrics, logs).
 * Collaborate with platform/cloud teams to deploy models and troubleshoot integrations.
 * Stay current with state-of-the-art AI applications and contribute improvements to models, tooling, and AI engineering practices.


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