Artificial Intelligence/Machine Learning (AI/ML) Engineer

• Requisition ID: 2387
• Standard Title:
• Required Security Clearance: Top Secret/SCI with Full Scope Polygraph
• Location: Annapolis Junction, MD
• Work Type: On-Site
• Shift: First
• Referral Eligibility: Eligible
• U.S. Citizenship Required? Yes

Base-2 Solutions is seeking an AI/ML Engineer who designs, creates, tests, and productizes AI/ML algorithms to solve business challenges. The AI/ML models they create should be capable of learning and making predictions as defined by the business logic developed to meet customer requirements. The AI/ML Engineer should be proficient in all aspects of model architecture, data pipeline interaction, and metrics application, interpretation, and presentation. The AI/ML Engineer needs familiarity with foundational concepts of application development, infrastructure management, data engineering, and data governance. Through an understanding of training, retraining, deploying, scheduling, monitoring, and improving models through iterative user and system feedback, the AI/ML Engineer designs and creates scalable solutions for optimal performance. The AI/ML Engineer may be responsible for leading geographically diverse teams and will often serve as a primary POC for AI-related matters, so must have exceptional analytical, problem-solving and communication skills.

Required Skills

• Experience with standard machine language frameworks, e.g. Pytorch, TensorFlow.
• Select appropriate data sets.
• Perform statistical analysis.
• Run machine learning algorithms.
• Use results to improve models.
• Train and retrain systems when needed.
• Experience in working with various ML libraries and packages.
• Run standard test and evaluation protocols.
• Provide system integration oversight.
• Oversee Test and evaluation of AI and ML algorithms through an iterative design process to meet verification and validation requirements.
• Research and implement a broad range of AI and ML algorithms and tools.
• Design or Select appropriate data and knowledge representation methods.
• Recognize software architecture, data modelling, and data structures.
• Transform and convert data science prototypes into scalable solutions.
• Verify data and model output quality.
• Identify differences in data distribution that affect model performance.

• Five (5) years experience in applied machine learning in programs and contracts of similar scope, type, and complexity is required.
• A Master's or Ph.D. degree in advanced math, artificial intelligence, data science, computer science or deep learning from an accredited college or university.
• Five (5) additional years of machine learning experience with a relevant Bachelor's degree may be substituted for a Master's degree.
  

• Expert knowledge with multiple programming languages, including:
• Python
• Java
• R
  

• Competitive fixed salary or hourly pay (based on experience, skills, location, and internal equity).
• Employee referral bonuses up to $10,000 per hired referral.
• Additional bonus opportunities for exceptional performance and contributions to business development and company growth (role-dependent).

• 100% company-paid medical premiums for employees and eligible dependents.
• Choose from multiple plan options with CareFirst, Kaiser, and UnitedHealthcare, including PPO, POS, HMO, and HSA-compatible plans.
• 100% company-paid dental premiums for employees and eligible dependents.
• 100% company-paid vision premiums for employees and eligible dependents.

• 100% company-paid premiums for short-term disability.
• 100% company-paid premiums for long-term disability.
• 100% company-paid premiums for accidental death & dismemberment (AD&D).
• 100% company-paid premiums for life insurance up to $200,000.

• 401(k) with immediate vesting: 4% company match plus a 4% non-elective company contribution (8% total).
• 401(k) pre-tax and Roth options.

• Up to 20 days of flexible paid time off (PTO).
• 11 paid floating holidays.

• Flexible work schedules, including flex time and compressed work periods (contract and project-dependent).