Machine Learning Engineer, SME

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.

Responsibilities:

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

Qualifications:

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.