AI/ML Engineer - Model Development - Secret Clearance

Cognitive Space, Inc.•Houston, TX

2d•$160,000 - $195,000•Hybrid

About The Position

We are seeking a highly skilled Machine Learning Engineer to join our innovative team who enjoys working in a dynamic and fast-paced environment while taking ideas from theory into deployment. You will play a crucial role in enhancing our CNTIENT-Optimize automated scheduling solution with cutting-edge machine learning algorithms and models. It is important for you to possess a passion for reinforcement learning (RL) or neural network models, managing complex data sets, and data fusion methodologies

Requirements

US Citizenship, Permanent Resident (Green) Card
Active Secret clearance or the ability to obtain and maintain one.
Bachelor’s, Master’s degree, or Ph.D. in a relevant field: Statistics, Applied Mathematics, Operations Research, Computational Physics, Computer Science, Engineering, etc.
2-5 years of professional experience as a Machine Learning Engineer, AI Engineer, Applied Scientist, or similar role using RL or neural networks.
Comprehensive knowledge of numerical methods, probability, and statistics.
Experience with Python, Rust, and with data science tools like Numpy and Pandas.
Deep knowledge of machine learning frameworks, including TensorFlow, PyTorch, and Keras.
Competence with Jupyter Notebook or similar platforms for development, testing, and presenting findings.
Experience in data manipulation, analysis, and visualization.
Proficiency in conveying intricate data in a clear and practical manner.

Responsibilities

Develop, train and deploy RL or GNN models to analyze and interpret complex data, enhancing predictive accuracy, and uncovering hidden patterns in large datasets, while ensuring compliance with operational specifications.
Design and implement data fusion algorithms to integrate information from multiple sources, ensuring real-time situational awareness.
Containerize decision-making algorithms and capabilities for on-edge deployment.
Collaborate with cross-functional teams to identify and prioritize AI/ML applications that address key milestones and requirements.