Pharma AI/ML Engineer | NLP, Generative AI, MLOps

MACHINE LEARNING TECHNOLOGIES LLC; Austin (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

Machine Learning Technologies LLC in Austin, TX seeks an experienced AI/ML Engineer to design, develop, and deploy intelligent applications solving complex business problems. You will build models, preprocess data, and integrate AI capabilities across enterprise systems to deliver measurable impact.

The role requires expertise in Python, ML libraries, NLP, and cloud AI platforms, with a focus on scalable pipelines and model governance.

Qualifications

• Designing and deploying ML models and AI-based solutions.
• Handling and preprocessing structured and unstructured data.
• Strong understanding of ML lifecycle and evaluation metrics.

Responsibilities

• Design, develop, and implement machine learning models and AI-based solutions.
• Collect, clean, preprocess, and analyze structured and unstructured datasets.
• Build predictive models using supervised and unsupervised learning techniques.
• Develop and optimize machine learning algorithms for business applications.
• Work with NLP, deep learning, and generative AI technologies.
• Integrate AI/ML models into existing enterprise applications.
• Collaborate with data engineers and software developers to build scalable AI solutions.
• Monitor model performance and implement continuous improvements.
• Develop automated machine learning pipelines and workflows.
• Document model architecture, development processes, and implementation results.

Skills

Python

SQL

Machine Learning

PyTorch

TensorFlow

Scikit-learn

NLP

Generative AI

LLMs

Data preprocessing

Tools

SageMaker

Vertex AI

Azure ML

MLOps

Model Deployment

Job description

Machine Learning Technologies LLC in Austin, TX seeks an experienced AI/ML Engineer to design, develop, and deploy intelligent applications solving complex business problems. You will build models, preprocess data, and integrate AI capabilities across enterprise systems to deliver measurable impact.

The role requires expertise in Python, ML libraries, NLP, and cloud AI platforms, with a focus on scalable pipelines and model governance.