AI Lead Engineer

ORBIS Inc

7d•Onsite

About The Position

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.

Requirements

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)
Solid foundation in: Statistical inference (Frequentist and Bayesian methods)
Solid foundation in: 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)

Nice To Haves

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)
Knowledge of: Data storage systems (relational and non-relational databases)
Interest or experience in defense, remote sensing, or space-based systems

Responsibilities

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)
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
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
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
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