Artificial Intelligence/Machine Learning (AI/MI) Engineer Skill Level 2

About the role

Design, create, test, and deploy AI/ML algorithms addressing complex business challenges. Develop AI/ML models that can learn and make predictions according to customer-defined business logic. Oversee all aspects of model architecture, data pipeline interaction, and metrics interpretation and presentation. Ensure optimal model performance through iterative feedback, monitoring, and improvement. Collaborate across diverse, often geographically spread teams, serving as the main point of contact (POC) for AI-related initiatives and guiding scalable, high-performing solutions.

Responsibilities

• Select appropriate datasets, perform statistical analysis, and run machine learning algorithms to improve model accuracy and performance.
• Train and retrain systems when necessary, demonstrating experience with various ML libraries and packages.
• Run standard test and evaluation protocols and provide system integration oversight.
• Oversee the test and evaluation of AI and ML algorithms through an iterative design process to ensure verification and validation requirements are met.
• Research and implement a broad range of AI and ML algorithms and tools, including selecting or designing appropriate data and knowledge representation methods.
• Transform data science prototypes into scalable solutions by recognizing and applying knowledge in software architecture, data modeling, and data structures.
• Verify data and model output quality, identify differences in data distribution that could affect model performance, with experience in standard machine learning frameworks such as PyTorch and TensorFlow.

Requirements

• Ability to select appropriate datasets, perform statistical analysis, and run machine learning algorithms to improve model accuracy and performance.
• Experience training and retraining systems when necessary, demonstrating experience with various ML libraries and packages.
• Experience running standard test and evaluation protocols and providing system integration oversight.
• Experience overseeing the test and evaluation of AI and ML algorithms through an iterative design process to ensure verification and validation requirements are met.
• Experience researching and implementing a broad range of AI and ML algorithms and tools, including selecting or designing appropriate data and knowledge representation methods.
• Experience transforming data science prototypes into scalable solutions by recognizing and applying knowledge in software architecture, data modeling, and data structures.
• Experience verifying data and model output quality, identifying differences in data distribution that could affect model performance, with experience in standard machine learning frameworks such as PyTorch and TensorFlow.
• Five years of experience in applied machine learning in programs and contracts of similar scope, type, and complexity, with a Master’s or Ph.D. in advanced math, artificial intelligence, data science, computer science, or deep learning from an accredited college or university.
• Five additional years of machine learning experience with a relevant Bachelor’s degree may be substituted for a Master’s degree.
• Active TS/SCI clearance with Polygraph required.

Qualifications

Must have the ability to select appropriate datasets, perform statistical analysis, and run machine learning algorithms to improve model accuracy and performance. Must be capable of training and retraining systems when necessary, demonstrating experience with various ML libraries and packages. Must possess the ability to run standard test and evaluation protocols and provide system integration oversight. Must be able to oversee the test and evaluation of AI and ML algorithms through an iterative design process to ensure verification and validation requirements are met. Must be experienced in researching and implementing a broad range of AI and ML algorithms and tools, including selecting or designing appropriate data and knowledge representation methods. Must recognize and apply knowledge in software architecture, data modeling, and data structures, and be able to transform data science prototypes into scalable solutions. Must be capable of verifying data and model output quality, identifying differences in data distribution that could affect model performance, with experience in standard machine learning frameworks such as PyTorch and TensorFlow. Must have five years of experience in applied machine learning in programs and contracts of similar scope, type, and complexity, with a Master’s or Ph.D. in advanced math, artificial intelligence, data science, computer science, or deep learning from an accredited college or university. Five additional years of machine learning experience with a relevant Bachelor’s degree may be substituted for a Master’s degree. Active TS/SCI clearance with Polygraph is required.

Skills

Proficiency in programming languages like Python, Java, C, and R is highly advantageous.

Benefits

At Kaizen Approach, we offer a competitive compensation, a robust benefits package that supports your well-being and growth, and a commitment to your happiness both at work and beyond. Our benefits include 4 weeks of PTO, 11 holidays, gifted 401k, profit sharing, and paid training. We prioritize well-being with premium healthcare, financial and family support, retirement planning, and ongoing learning.

Pay

A variety of factors can impact the final salary offered, including, but not limited to, geographic location, Federal Government contract labor categories and wage rates, relevant work experience, specialized skills and competencies, education, and certifications.

Schedule

N/A

Benefits

N/A

Pay

A variety of factors can impact the final salary offered, including, but not limited to, geographic location, Federal Government contract labor categories and wage rates, relevant work experience, specialized skills and competencies, education, and certifications.