AI SME / Developer

eSimplicity•Columbia, MD

5d•Hybrid

About The Position

We are seeking an experienced AI SME / Developer to oversee quality assurance activities across our products and systems. This role is responsible for apply expertise in computer science and scientific disciplines to build, optimize, and maintain software applications used for scientific research, data analysis, and modeling.

Requirements

All candidates must pass public trust clearance through the U.S. Federal Government. This requires candidates to either be U.S. citizens or pass clearance through the Foreign National Government System which will require that candidates have lived within the United States for at least 3 out of the previous 5 years, have a valid and non-expired passport from their country of birth and appropriate VISA/work permit documentation.
Bachelor’s degree in Computer Science, Engineering, Data Science, Mathematics, or related technical field
5+ years of experience in software engineering, data science, or AI/ML development.
Demonstrated experience with: Python, R, or similar programming languages, Machine learning frameworks, Data engineering and large-scale data processing, and Model deployment and MLOps pipelines?
Experience implementing AI solutions in secure or regulated environments.

Nice To Haves

Strong Understanding of AI/ML Concepts
Machine learning fundamentals (supervised, unsupervised, reinforcement learning)
Deep learning architectures (CNNs, RNNs, transformers, LLMs)
Model evaluation, tuning, explainability, and bias mitigation
HandsOn Experience With AI Tools & Frameworks such as:
Python + ML libraries (TensorFlow, PyTorch, Scikitlearn)
Working knowledge of LLM tooling (e.g., LangChain, vector databases, RAG)
MLOps platforms (Azure ML, AWS SageMaker, MLflow)
Data Expertise
Data processing / feature engineering
Understanding of structured and unstructured data
Ability to work with large datasets and ETL workflows
Ability to Translate Business Problems Into AI Solutions
Identify use cases
Evaluate feasibility
Propose architectures and approaches
Communicate tradeoffs clearly to nontechnical stakeholders
Experience Leading AI Initiatives
Running proofofconcepts
Advising on model deployment
Working with crossfunctional teams (product, engineering, legal, compliance, UX)
Understanding of Governance, Ethics, and Responsible AI
AI fairness, safety, bias, and transparency
Data privacy laws (GDPR, CCPA, etc.)
Model governance and lifecycle documentation
Risk assessments and policy alignment

Responsibilities

Serve as the technical authority for AI/ML strategy, architecture, and implementation across the program.
Design and deploy scalable AI/ML models
Lead development of predictive analytics, automation frameworks, and intelligent decision-support systems.
Integrate AI solutions into secure enterprise environments.
Ensure compliance with data governance standards.
Provide oversight of data engineering pipelines and model lifecycle management (MLOps).
Develop and maintain model validation, explainability, and bias mitigation practices.
Advise program leadership and government stakeholders on emerging AI technologies and mission applications.
Support transition of experimental or prototype AI capabilities into operational production systems.
Mentor junior engineers and provide technical leadership across cross-functional teams.?