AI/ML Engineer: Build Scalable Intelligent Solutions

Valiant Technologies LLC; Austin (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

Valiant Technologies LLC is seeking an experienced AI/ML Engineer to design, develop, and deploy intelligent applications addressing complex business problems. The role emphasizes practical model development and data-driven decision making.

The ideal candidate will work across data engineering and software teams, iterating on NLP, generative AI, and production-grade ML pipelines, with an emphasis on scalable, reliable solutions.

Qualifications

• Strong experience in ML model development and deployment.
• Proficient in Python, SQL and ML tooling.
• Experience with NLP, Generative AI, and LLMs.
• Familiar with MLOps and data preprocessing.

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

TensorFlow

PyTorch

Scikit-learn

NLP

Generative AI

LLMs

Prompt Engineering

Data Processing

Feature Engineering

Model Deployment

MLOps

Statistical Analysis

Predictive Modeling

Tools

TensorFlow

PyTorch

Scikit-learn

Job description

Valiant Technologies LLC is seeking an experienced AI/ML Engineer to design, develop, and deploy intelligent applications addressing complex business problems. The role emphasizes practical model development and data-driven decision making.

The ideal candidate will work across data engineering and software teams, iterating on NLP, generative AI, and production-grade ML pipelines, with an emphasis on scalable, reliable solutions.