Machine Learning Engineer

This role applies machine learning and NLP techniques to develop and adapt Large Language Models (LLMs) that improve analytic workflows and help answer intelligence questions using both structured and unstructured data. The position includes building models, analytics, ETL pipelines, and reports in a team setting.

Key Responsibilities

• Leverage open source, best-in-class models to create reusable and repurposable model artifacts using fine-tuning, transfer learning, and ensembles, including domains such as classification.
• Develop supervised model approaches using open source architectures such as CNN, Unet, YOLO, or similar.
• Create unsupervised approaches using methods such as DBSCAN, K-Nearest, Adaboost, or similar.
• Build prediction-oriented models, including predictors such as LSTM, UConv, or similar.
• Develop regressors including Bayesian, linear, or similar.
• Implement fusion approaches at the sensor level and entity level.
• Support decision-making model development, including task assignments, combinational and parametric optimizations, reinforcement learning, path planning, or similar.
• Develop generative model solutions, including LLMs and stackable LLM approaches, using fine-tuning, transfer learning, and ensembles.
• Apply AI/ML, deep learning, NLP, recommendation, threat detection, computer vision, data mining, statistics, and related methods using appropriate frameworks such as TensorFlow and PyTorch.
• Analyze large volumes of raw data, including text, to determine suitability for training or testing AI models.
• Preprocess and 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.
• Collaborate with the team to author analytic publications and produce ad-hoc reports with data visualizations aligned to sponsor templates; document methods in GitHub.
• Implement the sponsor’s existing coordination process.
• Provide ad-hoc technical education to staff.
• Deliver subject matter expertise in AI/ML to support sponsor initiatives.

Required Qualifications

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

Technology Stack

• 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 Note

• 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 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 for text classification and topic modeling in Python using standard machine learning (SciKit Learn) or deep learning models.
• Demonstrated experience developing applications for semantic search.
• Proficiency with Tableau to produce visualizations and dashboards.
• 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).

Location and Salary

Location: McLean, VA (onsite).

Salary: USD 190,000 per year (salary is commensurate with education and experience; up to $190K).