Machine Learning Engineer

Dezign Concepts LLC is seeking a Machine Learning Engineer to develop and adapt Large Language Models (LLMs) and NLP methods that strengthen analytic workflows and support intelligence questions. This onsite role in McLean, VA focuses on building models, analytics, ETL pipelines, and reporting capabilities while collaborating with a team to deliver reusable AI/ML solutions.

The position centers on working with structured and unstructured data, including text, to determine how it can be used for training and testing. You will also analyze Sponsor data, implement preprocessing and advanced data engineering, and apply your AI/ML expertise to validate model performance and communicate results.

Responsibilities

• Leverage open source best-in-class models to create new models through fine tuning, transfer learning, and other techniques, including ensemble approaches that can be re-purposed and reused across domains.
• Develop models for classification, including supervised approaches such as CNN, Unet, YOLO, or similar.
• Build unsupervised models such as DBSCAN, K-Nearest, Adaboost, or similar.
• Create prediction solutions including predictors such as LSTM, UConv, or similar.
• Develop regressors including Bayesian, linear, or similar methods.
• Apply fusion methods at the sensor level and entity level.
• Support decision-making use cases, including task assignments, combinational and parametric optimizations, Reinforcement Learning, path planning, or similar approaches.
• Develop generative capabilities using LLMs, stackable LLMs, or similar.
• Apply AI/ML, deep learning, and NLP methods using frameworks such as TensorFlow and PyTorch, including text classification, NLP, topic and language modeling, sentiment analysis, information retrieval, recommender systems and personalization, threat detection, computer vision, data mining, statistics, or related methods.
• Analyze large volumes of raw data, including text, to determine utility for training or testing AI models.
• Preprocess or clean structured and unstructured Sponsor data, including text data.
• Design and implement advanced ETL code and table configurations for complex data sets.
• Use SQL to develop and organize relevant information.
• Work in a team environment to author analytic publications and produce ad-hoc reports, including data visualizations using Sponsor templates, and document methods in GitHub.
• Implement the Sponsor’s existing coordination process.
• Provide ad-hoc technical education to staff.
• Provide AI/ML subject matter expertise to support Sponsor initiatives.

Requirements

• Must be a US Citizen.
• Active Top Secret SCI with Poly clearance is required.
• Minimum Bachelor’s Degree required.
• Expert level experience required.
• Demonstrated experience tuning neural networks (including LLMs) on custom data sets and applying results to specific use cases.
• Demonstrated professional or academic experience using Python or R.
• (KEY) Demonstrated experience developing models and ensembles, including selecting the best Python libraries for the task, choosing appropriate pre-processing actions, performing analysis, and assessing model performance.
• (KEY) Demonstrated experience testing, evaluating, or validating AI systems with a focus on LLM-based systems.
• (KEY) Demonstrated experience in experiment design and execution to test LLM performance against a benchmark.
• (KEY) Demonstrated experience with deep learning frameworks such as PyTorch, Tensorflow, or Keras.
• (KEY) Demonstrated proficiency with SQL, including common table expressions, set operations, aggregated functions, and nested subqueries.
• (KEY) Demonstrated experience leveraging GPUs for accelerated computing.
• Demonstrated experience with version control systems such as GitHub and Jenkins.

Technologies

• Python, R, SQL
• TensorFlow, PyTorch, Keras
• CNN, Unet, YOLO
• DBSCAN, K-Nearest, Adaboost
• LSTM, UConv
• Bayesian
• Reinforcement Learning, Path Planning
• LLMs, Stackable LLMs
• Github, Jenkins
• GPUs
• HuggingFace Transformers library, HuggingFace hub
• Flask
• SciKit Learn
• Tableau
• ONNX

Benefits

• Medical, Dental, Vision, Health Savings Account and more.
• Paid Time Off, Holidays, Social Events, Employee Assistance Program, and Team Building
• 401K, Tuition Assistance, Annual and Referral Bonuses

Security Clearance

• Active Top Secret Clearance with Poly Required
• Please note: This job requires an existing Top Secret Clearance and Polygraph

Travel

• Local travel/POV will be on an as needed basis, within the local place of performance.

Highly Desired (Not Required)

• Demonstrated professional or academic experience with the HuggingFace Transformers library and hub.
• Demonstrated experience with cloud computing development and architecture.
• Demonstrated experience with front-end web development frameworks such as Flask.
• Demonstrated experience creating machine learning models that conduct text classification and topic modeling in Python using standard machine learning (SciKit Learn) or deep learning models.
• Demonstrated experience developing applications for semantic search.
• Demonstrated professional or academic experience and proficiency with Tableau to produce visualizations and dashboards.
• Demonstrated academic or professional experience communicating methodological choices and model results.
• Demonstrated experience with verification and validation test benches.
• Demonstrated experience with Explainable AI (XAI) techniques.
• Demonstrated experience with ONNX (Open Neural Net Exchange).

Salary: Up to $190,000 per year, with compensation commensurate with education and experience.