Senior Data Engineer

Location: Irving, Tx

Assignment Type: 6 Month Contract-to-hire

Compensation: 125k-150k

Work Model: 4 days on-site, 9:00am-5:00pm

The Full-Stack AI/ML Engineer will work on high-impact initiatives supporting the company's digital transformation in the electrical distribution space.

• Building and implementing AI-powered chatbots for companys customer-facing applications to streamline communication, enhance user experience, and improve service efficiency.
• Designing and integrating machine learning models focused on pricing optimization and sales forecasting
  , helping the business make data-driven decisions and improve profitability.
• Collaborating cross-functionally with product, data, and engineering teams to bring AI models from prototype to production within companys technology ecosystem.

Ideal candidates will have experience across the full AI/ML development stack — from data preparation and model development to application integration and deployment — and be excited to apply their technical expertise in a fast-moving, customer-focused business environment.

• Design and build AI/ML solutions that automate, optimize, or enhance business workflows.
• Acquire and preprocess structured/unstructured data from diverse sources (APIs, databases, OCR pipelines, documents, etc.).
• Conduct Exploratory Data Analysis (EDA) and develop statistical and predictive models using Python and ML frameworks.
• Build and fine-tune Large Language Model (LLM) pipelines (e.g., OpenAI, Azure OpenAI, Hugging Face, Lang Chain).
• Implement retrieval-augmented generation (RAG) and document‑intelligence systems.
• Develop and deploy production‑grade APIs and microservices using FastAPI or similar, integrated with MLOps practices.
• Collaborate with data engineers to ensure efficient data pipelines and with software engineers to integrate models into products.
• Continuously monitor, retrain, and optimize deployed models.
• Research and prototype emerging AI methods—multimodal models and AI agents.
• Document architecture, design choices, and experiment outcomes for transparency and reproducibility.
• Work as a core member of a cross‑functional AI team, contributing to sprint planning, backlog grooming, daily stand‑ups, and retrospectives under Scrum / Agile frameworks.
• Participate in peer code reviews, ensure clean coding practices, and contribute to shared libraries and internal AI frameworks.