Bachelor's degree in Computer Science, Data Science, Mathematics, Engineering, or related field (Master's or Ph.D. preferred).
Experience developing and tuning machine learning, deep learning, and LLM-based solutions.
Proficiency in Python and/or R for machine learning and data analytics.
Strong SQL expertise, including CTEs, set operations, aggregate functions, and nested subqueries.
Experience with deep learning frameworks like PyTorch, TensorFlow, and Keras.
Hands-on experience testing and validating AI systems, particularly LLM applications.
Experience leveraging GPUs for AI/ML workloads.
Responsibilities
Design, develop, fine-tune, and optimize machine learning and deep learning models for mission-focused use cases.
Develop AI/ML pipelines, including data preprocessing, feature engineering, and model training.
Conduct benchmarking and validation to assess AI system effectiveness, focusing on LLM solutions.
Build and evaluate model ensembles, identifying optimal algorithms and frameworks.
Leverage GPU-accelerated environments to enhance model training and inference performance.
Develop applications for semantic search and natural language processing capabilities.
Collaborate with cross-functional teams to translate operational requirements into AI solutions.
Benefits
Opportunity to work with cutting-edge AI and ML technologies.
Collaborative environment with cross-functional teams.
Focus on mission-driven projects with real-world impact.
Access to advanced computing resources and tools.
Potential for professional growth and development in AI/ML.
Full 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.
