Staff AI/ML Engineering Manager (TS/SCI) {S}
About the role
This position is for an AI/ML Engineering Manager. ARKA-Mission Applications is seeking a talented and motivated AI/ML Engineering Manager to join our growing team.
Responsibilities
Management & Leadership (Approx. 25% on average): Lead & Mentor: Manage, coach, and mentor a team of AI/ML engineers, fostering their technical and professional growth, by providing career advice and helping with program technical guidance. Additionally, you will work with the greater AI/ML engineering group to cultivate a positive, collaborative, inclusive, and high-performing team that is focused on bringing modern AI/ML development practices and robust engineering principles across all ARKA programs.
Performance Management: Conduct regular 1:1 bi-weekly meetings with your team, provide feedback on both technical and non-technical topics, assist with setting clear goals, and manage performance reviews for your direct reports.
Collaboration: Work closely with AI/ML engineering organization and other engineering leadership to align priorities, define requirements, and ensure successful project delivery across programs.
Project Oversight: Help manage project priorities, timelines, and deliverables for your team, identifying and removing roadblocks.
Hiring & Onboarding: Participate in the recruitment, interviewing, onboarding, and retention of engineering talent for your team and the broader organization. Additionally works closely with engineering leadership to align current and new staff skillsets with program needs over time.
Technical Contribution (Approx. 75% on average)
Hands-on AI/ML Development: Actively participate in the end-to-end machine learning lifecycle, contributing high-quality, well-tested, and maintainable code for data pipelines, model training, evaluation, and deployment to key AI/ML projects using our tech stack.
Proven proficiency in Python, including experience with key machine learning libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy).
ML System Design & Architecture: Contribute to technical design discussions and architectural decisions for scalable and robust machine learning systems, including data pipelines, model training infrastructure, serving layers, and MLOps frameworks.
Code & Model Quality: Actively participate in code reviews, ensuring adherence to coding standards, MLOps best practices, and high-quality engineering principles, specifically for machine learning models and infrastructure (e.g., reproducibility, testability, explainability).
Stay Current and Mentor: Keep abreast of cutting-edge machine learning research, algorithms, MLOps tools, and cloud AI/ML services, advocating for their strategic adoption. Leverage this continuous learning to mentor and provide technical direction to your AI/ML team.
Required Qualifications
Bachelor’s degree in computer science, data science, mathematics, engineering, or a related field
3+ years of experience in a formal or informal leadership capacity (e.g., Tech Lead, Team Lead, mentoring junior engineers, project leadership)
8+ years of experience developing AI/ML applications, data science, or algorithm development
Experience with Python and data science / machine learning libraries (e.g. PyTorch, TensorFlow, Keras, OpenCV, NumPy, Pandas, Polars, scikit-learn, etc.)
Experience with one or more of the following areas:
Applying unsupervised and/or supervised machine learning techniques
Applying and/or developing algorithms based in statistical analysis
Analyzing large datasets and building models to perform inference
Applying Large Language Models (LLMs) and techniques such as retrieval augmented generation (RAG), fine tuning, and prompt engineering
Experience with deep learning architectures (e.g. FCNs, CNNs, RNNs, Transformers, GANs)
Experience with modern software development methodologies (Agile, Scrum, Kanban)
Experience with version control systems such as Git and the associated tooling to for modern software version control
Excellent communication, interpersonal, and collaboration skills
Strong problem-solving and analytical abilities
A genuine passion for both technology and people leadership
Ability to effectively balance management responsibilities with individual technical contributions
Active TS/SCI U.S. Government Security Clearance
Preferred Qualifications
MS or PhD in machine learning, computer science, mathematics, or related fields
Experience directly managing AI/ML engineers, including performance management cycles
Experience with any of the following AI/ML domains:
Large Language Models and experience identifying ways to incorporate them into new areas and applications
Applying Transformer-based architectures to domains in other areas outside of Natural Language Processing (NLP) such as computer vision
Object detection algorithms such as YOLO and Faster-RCNN
Natural Language Processing algorithms such as BERT
Generative Adversarial Networks and Variational Autoencoders
Reinforcement learning and familiarity with Gymnasium Gym, RLlib, and Stable Baselines
Applying clustering algorithms and/or deep neural networks to real life problems
Implementing tracking and pattern-of-life algorithms
Experience with Machine Learning libraries and frameworks such as HuggingFace and LangChain
Experience with Computer Vision libraries such as OpenCV, Nerfstudio, FiftyOne, etc.
Experience with Linux
Familiarity with using AWS cloud computing resources such as EC2, S3, Lambda, etc.
Experience with any of the following additional languages: Java, C++, Rust, Go, and/or C#
Experience implementing algorithms on the GPU in Python or C++ using CUDA and other CUDA libraries
Experience in application deployment, virtualization, and containerization (e.g. Podman, Docker, Kubernetes, Rancher)
Experience working with various Remote Sensing datasets (e.g. EO/OPIR/SAR images, passive RF, etc.)
Pay Range
$160,000 - $200,000
Your actual level and base salary will be determined on a case-by-case basis and may vary based on the following considerations: job-related knowledge and skills, education, and experience.
Location
Aurora, CO