AI/ML Engineer: NLP & Generative AI Deployments

Robotic Technologies Automation; City of Albany (NY); On-site; USD 120,000 - 180,000; Full time

Job summary

Robotic Technologies Automation is seeking an experienced AI/ML Engineer to design, develop, and deploy AI/ML solutions. The role requires strong programming skills, ML/DL expertise, data processing, and model deployment across modern frameworks.

The ideal candidate will design, implement, and optimize models, work with large datasets, and deploy AI services via REST APIs and cloud platforms. Collaboration with data scientists and engineers is essential to success.

Qualifications

• Proficient in Python, SQL, and R.
• Experience with ML/DL frameworks and model deployment.
• Familiarity with NLP, LLMs, and generative AI is a plus.

Responsibilities

• Design, develop, and implement ML/AI models and solutions.
• Build predictive models using supervised and unsupervised techniques.
• Develop AI-powered apps using Python and ML frameworks.
• Work with large datasets for preprocessing, feature engineering, and training.
• Implement deep learning models with TensorFlow and PyTorch.
• Develop NLP solutions for text classification and sentiment analysis.
• Build and deploy AI/LLM apps and services.
• Collaborate with data scientists, data engineers, and software teams.
• Monitor model performance and scalability; tune hyperparameters.
• Deploy models on cloud platforms (AWS, Azure, GCP).

Skills

Python

SQL

R

Machine Learning

Deep Learning

TensorFlow

PyTorch

Scikit-learn

NLP

LLMs

REST APIs

Microservices

Tools

Docker

Kubernetes

Job description

Robotic Technologies Automation is seeking an experienced AI/ML Engineer to design, develop, and deploy AI/ML solutions. The role requires strong programming skills, ML/DL expertise, data processing, and model deployment across modern frameworks.

The ideal candidate will design, implement, and optimize models, work with large datasets, and deploy AI services via REST APIs and cloud platforms. Collaboration with data scientists and engineers is essential to success.