Overview

We are looking for seasoned Machine Learning Engineer to work with our existing team of Data Scientists and Engineers to use AI/ML technology in supporting Federal use cases.  We are looking for a more than just a "Machine Learning Engineer", but a technologist with excellent communication and customer service skills and a passion for data and problem solving.

Responsibilities

• Collaborate with cross-functional teams to design and develop machine learning models and algorithms to address business needs.
• Analyze and process large datasets to extract meaningful insights and patterns.
• Collaborate with cross-functional teams to integrate machine learning solutions into existing systems and workflows.
• Optimize and fine-tune machine learning models for performance, scalability, and accuracy.
• Implement and maintain data pipelines to support machine learning workflows.
• Evaluate the effectiveness of machine learning models using appropriate metrics and validation techniques.
• Document processes, experiments, and results to ensure reproducibility and knowledge sharing.
• Deploy machine learning models to production environments and monitor their performance.
• Stay updated with the latest research and trends in AI to implement cutting-edge solutions.
• Support an Agile software development lifecycle
• You will contribute to the growth of our AI & Data Exploitation Practice!

Qualifications

• Ability to hold a position of public trust with the US government.
• Bachelor's degree in computer science, data science/statistics, information systems, engineering, business, or a scientific or technical discipline
• 2-4 years industry experience developing ML/AI solutions and a passion for solving complex problems.
• 2-4 years industry experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn.
• Strong programming skills in languages such as Python, R, or Java.
• Solid understanding of statistical methods, data structures, and algorithms.
• Experience with data preprocessing, feature engineering, and model evaluation techniques.
• Familiarity with big data technologies like Hadoop, Spark, or similar.
• Knowledge of cloud platforms such as AWS, Google Cloud, or Azure.
• Experience with version control systems, such as Git, and continuous integration/continuous deployment (CI/CD) practices.
• Excellent problem-solving skills and attention to detail.
• Strong communication skills and ability to work collaboratively in a team environment.
• Ability to manage multiple tasks and projects simultaneously while meeting deadlines.