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Augment Professional Services (APS)

Principal Data Scientist

Posted 6 Days Ago
In-Office
77002, Houston, TX
200K-250K Annually
Entry level
In-Office
77002, Houston, TX
200K-250K Annually
Entry level
Leads the design, development, and deployment of production-scale AI and machine learning systems. Builds solutions using LLMs, generative AI, NLP, computer vision, and deep learning; architects ML pipelines; optimizes models through fine-tuning and prompt engineering; translates technical results into business strategies; partners with stakeholders; communicates outcomes; and mentors data scientists while establishing MLOps best practices.
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About Augment Professional Services (APS)

Augment Professional Services (APS) delivers specialized talent, consulting expertise, and project support to organizations operating in complex technical environments. Our teams partner with clients across the Technology, Energy, Utilities, and EPC sectors to support critical initiatives in digital transformation, data and analytics, infrastructure modernization, and engineering delivery.

Through a flexible services model that includes managed services, project-based delivery, and embedded technical expertise, APS helps organizations accelerate innovation, scale capabilities, and execute high-impact initiatives with confidence.

Position Overview

We are seeking a Principal Data Scientist with deep expertise in Artificial Intelligence, Large Language Models (LLMs), Natural Language Processing (NLP), Computer Vision (CV), and Generative AI.

This role will serve as a technical leader and architect of AI-driven solutions, responsible for designing, building, and deploying advanced machine learning systems that deliver measurable business impact. The ideal candidate brings both strong technical depth and the ability to translate complex AI methodologies into real-world applications.

The Principal Data Scientist will work closely with cross-functional stakeholders, engineers, and leadership to drive innovation through scalable AI solutions and production-ready machine learning systems.

Key responsibilities include:

  • Designing and developing advanced machine learning and deep learning models

  • Building solutions leveraging Large Language Models (LLMs), Generative AI, NLP, and Computer Vision

  • Architecting scalable AI and ML pipelines from experimentation through production deployment

  • Developing and optimizing models through fine-tuning, prompt engineering, and inference optimization

  • Building end-to-end machine learning workflows including data ingestion, feature engineering, training, evaluation, deployment, and monitoring

  • Translating complex data science methodologies into actionable insights and business strategies

  • Partnering with business leaders to identify opportunities where AI can drive innovation and operational efficiency

  • Communicating technical concepts and model outcomes to both technical and non-technical stakeholders

  • Mentoring data scientists and helping establish best practices for model development and MLOps

QualificationsRequired Technical Skills Position Overview
  • Strong expertise in Artificial Intelligence and Machine Learning, including:

    • Natural Language Processing (NLP)

    • Computer Vision (CV)

    • Generative AI

    • Deep Learning

  • Hands-on experience working with:

    • Large Language Models (LLMs)

    • Prompt engineering and model fine-tuning

    • Multi-agent AI architectures

    • Model optimization and inference efficiency

  • Experience building and deploying production-scale machine learning systems

  • Proficiency with modern ML frameworks and ecosystems such as:

    • Python

    • PyTorch or TensorFlow

    • Hugging Face

    • LangChain or similar LLM frameworks

  • Familiarity with MLOps practices, scalable AI infrastructure, and data pipelines

Required Soft Skills
  • Curious and Innovative: Passionate about solving complex business problems using data and AI

  • Ownership and Initiative: Ability to drive projects from concept through deployment

  • Business Acumen: Understanding of how AI and machine learning solutions support business outcomes

  • Effective Communication: Ability to explain technical models and AI methodologies to non-technical audiences

  • Collaborative Leadership: Ability to work effectively across engineering, product, and business teams

Preferred Qualifications
  • Master’s or Ph.D. in a quantitative field such as:

    • Computer Science

    • Data Science

    • Statistics

    • Engineering

    • Applied Mathematics

    • Economics

  • Experience developing and deploying Generative AI or deep learning models in production environments

  • Experience working with large-scale datasets and enterprise AI platforms


Equal Opportunity Statement

Augment Professional Services and our client partners are committed to fostering inclusive and diverse workplaces. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected characteristic in accordance with applicable laws.

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