AI Machine Learning Engineer

Job Title: AI Machine Learning Engineer

Location: Ashburn, VA (Onsite)

Job Responsibilities Include :

Model Development & Implementation

• Evaluate, fine-tune, and implement machine learning models, including large language models (LLMs), focusing on adapting existing models to meet specific business needs.
• Build and train ML models, including defining preprocessing, feature engineering, validation strategies, and hyperparameter tuning.
• Analyze ML algorithms for suitability, assess error patterns, and develop strategies for continuous model improvement.
• Identify opportunities for transfer learning and relevant training datasets.
  

Data Engineering & Infrastructure

• Build data ingestion and transformation pipelines to support model training and deployment.
• Verify data quality, perform data cleaning, and oversee data acquisition processes as needed.
• Design and implement enterprise ML platforms, feature stores, and SDKs to support reproducible, scalable ML applications.
• Author and maintain Python packages for data science and engineering teams.
  

Deployment & Integration

• Deploy models to production and create APIs to integrate AI models into business operations.
• Support the migration and monitoring of cloud-based NLP environments.
• Drive cybersecurity practices in AI platform deployments.
  

Research & Innovation

• Lead R&D of GenAI tools, including staffing and coding assistants for federal agencies.
• Develop and evaluate AI-driven tools such as pull request classifiers and coding support tools.
• Architect and operationalize vectorization pipelines for structured and unstructured data.
  

Technical Leadership & Strategy

• Provide technical leadership in AI technologies, including GenAI, machine learning, deep learning, and natural language processing (NLP).
• Ensure the technical quality of AI solutions, including architecture, design, implementation, and deployment.
• Scope, plan, and manage complex AI projects from inception to delivery.
• Help AI product managers and business stakeholders understand the potential, limitations, and results of AI models.
  

Collaboration & Client Engagement

• Collaborate with cross-functional teams, including engineers, data scientists, business analysts, and client partners.
• Build strong relationships with clients, understand their challenges, and propose tailored AI/ML solutions.
  

Basic Qualifications:

• Minimum 7 years of experience in AI/ML engineering, software development, or related fields.
• Minimum 4 years of experience delivering GenAI solutions and scalable ML Ops platforms in enterprise and federal agency contexts.
• Minimum 4 years of software engineering foundation experience in Python.
• Minimum 4 years of experience in ML/AI platforms including Databricks, SageMaker, Snowflake, and Vertex AI.
• Minimum 3 years of experience with AI frameworks (such as TensorFlow, PyTorch) and building and deploying AI models .
• Minimum 1 year of experience managing engineering teams and mentoring junior talent.
  

Preferred Qualifications:

• AI / ML certification(s) from any of the MAAG Clouds / renowned 3rd party platforms
• Experience developing SDKs, CLI tools, and automation scripts.
• Exposure working with LLM Architecture / fine-tuning LLM s
• Knowledge of generative models, GAN s and transformer-based models
• Knowledge of ethical standards related to AI
• Proficiency in programming languages
• Strong communicator with the ability to engage technical and non-technical stakeholders.
• Active contributor to the broader AI/ML community.