AI Lead Engineer
Charleston, SC
Position Overview
We are seeking an AI Lead Engineer who combines strong hands-on technical ability with emerging leadership and product instincts. This role is ideal for someone who has worked in a startup or fast-paced environment, understands how AI systems move from prototype to real-world deployment, and is ready to grow into a team leadership position.
You will initially operate as a primary contributor, designing models, building training pipelines, and delivering AI-driven features, while helping shape the technical direction of our AI efforts. As products mature, you will take on increasing responsibility for mentoring junior engineers and building a small, high-performing team.
Key Responsibilities
Hands-On AI Development
- Design, build, and train machine learning and deep learning models (CNNs, transformers, RL, etc.)
- Develop scalable training pipelines and data processing workflows
- Work across the stack: data ingestion, model development, evaluation, and deployment
- Build and maintain AI systems (backend and, where applicable, user-facing interfaces)
Applied Product Development
- Translate AI capabilities into deployable features aligned with business needs
- Balance model performance with real-world constraints (latency, cost, reliability)
- Collaborate with stakeholders to prioritize features and iterate quickly
- Contribute to system architecture decisions as products evolve
Emerging Technical Leadership
- Provide guidance and informal mentorship to junior engineers
- Help establish coding standards, experimentation practices, and development workflows
- Participate in hiring as the team grows
- Gradually take ownership of technical direction for AI initiatives
R&D and Innovation
- Explore and prototype new approaches, including novel neural network architectures
- Apply advanced statistical inference and predictive modeling techniques
- Support exploration of emerging domains such as remote sensing, autonomy, or SBIRS-like systems
- Stay current with advancements in deep learning and applied AI
Collaboration & Execution
- Work within an Agile framework, contributing to sprint planning and regular updates
- Collaborate cross-functionally to support company growth through AI capabilities
- Maintain clear documentation of models, systems, and experiments
Required Qualifications
Bachelor's or Master's degree in Computer Science, Mathematical Sciences, Data Analytics, or related field
US Citizen with ability to obtain Secret Security Clearance
3-7 years of experience in AI/ML development (industry or applied research)
Strong programming skills in Python (C++ / Rust / JavaScript a plus)
Experience with deep learning frameworks such as PyTorch or TensorFlow
Solid foundation in:
Machine learning and deep learning (CNNs, RNNs, transformers)
Statistical inference (Frequentist and Bayesian methods)
Data processing and normalization techniques
Experience building and training models on real-world datasets (not just academic exercises)
Familiarity with version control systems (e.g., Azure DevOps, Git)
Preferred Qualifications
Experience in a startup or fast-paced product environment
Exposure to deploying models into production environments
Familiarity with MLOps concepts (model versioning, monitoring, pipelines)
Experience with image processing (OpenCV, Pillow) and structured/unstructured data
Knowledge of:
Advanced mathematics (e.g., tensor calculus, graph theory)
Data storage systems (relational and non-relational databases)
Interest or experience in defense, remote sensing, or space-based systems
What We're Looking For
- Someone who enjoys both building and leading
- Comfortable with ambiguity and wearing multiple hats
- Able to connect technical decisions to business outcomes
- Motivated by growth into a future leadership role
Growth Path
This role is designed to evolve into a formal leadership position. As our AI capabilities and product portfolio expand, you will have the opportunity to:
- Build and lead a small AI team
- Own major technical initiatives end-to-end
- Contribute to product and R&D strategy