Machine Learning Engineer, SME

VTG Defense; McLean (VA); On-site; USD 180,000 - 230,000; Full time

Job summary

VTG Defense is seeking a highly skilled Machine Learning Engineer SME to develop, evaluate, and deploy AI/ML solutions, focusing on LLMs and scalable architectures. You will design, fine-tune, and benchmark models, build pipelines, and collaborate across teams to translate operational needs into AI-enabled capabilities.

The role requires deep experience with PyTorch/TensorFlow, Python/R, SQL, and GPU-accelerated computing.

Qualifications

• Bachelor's degree in a technical field (Master's or PhD preferred).
• Experience developing and tuning ML/LLM solutions.
• Proficiency in Python and/or R for ML and data analytics.
• Experience with PyTorch, TensorFlow, and Keras.
• Strong SQL with CTEs, set operations, aggregates, and nested subqueries.
• Experience with GitHub and Jenkins for CI/CD and version control.
• Experience with GPUs/HPC for AI workloads.
• Hands-on testing, validating, evaluating AI systems (LLM-based).

Responsibilities

• Design, develop, fine-tune, and optimize ML/LLM models for mission-focused use cases.
• Build AI/ML pipelines, preprocess data, engineer features, train models, and evaluate performance.
• Benchmark, test, validate, and experiment to assess AI system reliability.
• Develop ensembles and select algorithms, frameworks, and Python libraries.
• Leverage GPU-accelerated compute for faster training and inference.
• Develop semantic search, information retrieval, and NLP capabilities.
• Collaborate with cross-functional teams to translate requirements into AI solutions.
• Create visualizations, dashboards, and reports to communicate model performance.
• Maintain code repos and follow software development best practices.

Skills

Python

R

SQL

PyTorch

TensorFlow

Keras

Hugging Face

Flask

Tableau

GitHub

Jenkins

NLP

LLMs

MLOps

Semantic Search

GPU Computing

Education

Bachelor's degree in Computer Science, Data Science, Mathematics, Engineering, or related field

Master's or Ph.D. preferred

Tools

GitHub

Jenkins

Flask

Tableau

Job description

Overview

We are seeking a highly skilled Machine Learning Engineer SME to support the development, evaluation, and deployment of advanced Artificial Intelligence (AI) and Machine Learning (ML) solutions, with a particular focus on Large Language Models (LLMs). The ideal candidate will possess deep expertise in model development, fine-tuning, benchmarking, and performance evaluation while leveraging modern AI frameworks, cloud technologies, and scalable computing architectures.

What will you do?

Key Responsibilities

• Design, develop, fine-tune, and optimize machine learning and deep learning models, including Large Language Models (LLMs), for mission-focused use cases.
• Develop AI/ML pipelines, perform data preprocessing, feature engineering, model training, and performance evaluation.
• Conduct benchmarking, testing, validation, and experimentation to assess the effectiveness and reliability of AI systems, with emphasis on LLM-based solutions.
• Build and evaluate model ensembles and identify optimal algorithms, frameworks, and Python libraries for specific applications.
• Leverage GPU-accelerated computing environments to improve model training and inference performance.
• Develop applications supporting semantic search, information retrieval, and natural language processing capabilities.
• Collaborate with cross-functional teams to translate operational requirements into AI-enabled solutions.
• Create visualizations, dashboards, and reporting solutions to communicate model performance and insights.
• Maintain code repositories and software development best practices using modern version control systems.

Required Qualifications

• Bachelor's degree in Computer Science, Data Science, Mathematics, Engineering, or a related technical field (Master's or Ph.D. preferred).
• Demonstrated professional or academic experience developing and tuning machine learning, deep learning, and LLM-based solutions.
• Proficiency in Python and/or R for machine learning and data analytics.
• Experience with deep learning frameworks such as:
  • PyTorch
  • TensorFlow
  • Keras
• Strong SQL expertise, including:
  • Common Table Expressions (CTEs)
  • Set operations
  • Aggregate functions
  • Nested subqueries
• Experience with version control tools such as GitHub and Jenkins.
• Experience leveraging GPUs and high-performance computing environments for AI/ML workloads.
• Hands‑on experience testing, validating, and evaluating AI systems, particularly LLM‑based applications.
• Experience designing and executing experiments to benchmark model performance.

Preferred Qualifications

• Experience with the Hugging Face Transformers ecosystem and model hub.
• Experience developing benchmarks and evaluation frameworks for LLM performance measurement.
• Knowledge of cloud‑based AI/ML architectures and development environments.
• Experience with web application development frameworks such as Flask.
• Experience building machine learning solutions for:
  • Text classification
  • Topic modeling
  • Natural language processing (NLP)
• Experience developing semantic search applications and retrieval solutions.
• Experience creating data visualizations and dashboards using Tableau.
• Familiarity with Scikit‑Learn and traditional machine learning techniques alongside deep learning methodologies.

Desired Technical Skills

• Large Language Models (LLMs)
• Generative AI
• Natural Language Processing (NLP)
• Machine Learning Operations (MLOps)
• Semantic Search
• Deep Learning
• GPU Computing
• Python
• SQL
• PyTorch
• TensorFlow
• Hugging Face
• Flask
• Tableau
• GitHub
• Jenkins

Do you have what it takes?

Clearances / Additional Requirements

• Ability to obtain and maintain any required government security clearance.
• Strong analytical, problem‑solving, and communication skills.
• Ability to work independently as a technical lead and trusted advisor in AI/ML initiatives.

Pay Range: VTG's estimated starting pay range is $180,000-$230,000 annually, which is a general guideline for the geographic location. When extending an offer, VTG also considers work experience, education, skill level, market considerations and may possibly include contractual requirements which may cause an offer to fall outside of this range.