REQUIRED: TO BE CONSIDERED FOR THIS POSITION YOU MUST HAVE AN ACTIVE TS/SCI W/ FULL SCOPE POLYGRAPH SECURITY CLEARANCE (U.S. CITIZENSHIP REQUIRED)
- The Artificial Intelligence/Machine Learning (AI/ML) Engineer 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.
- Expert knowledge of multiple programming languages, e.g. Python, Java, C, R, a plus.
- 10 years experience deploying machine learning algorithms 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 is required.
- 7 additional years machine learning experience with a relevant Bachelor's degree may be substituted for a Master's degree.
- Demonstrated abilities in software engineering and AI/ML model test and evaluation.
Responsibilities
- 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
- Develop criteria for test and evaluation to include explainability and resiliency
- Deep understanding of AI logic, semantics, ontologies, and knowledge representation
- Demonstrated ability to design, evaluate, and productize AI/ML models on a range of commercial cloud-based architectures
- Design ML algorithms according to customer requirements
- Research, experiment with, and implement suitable ML algorithms and tools
- Broaden current AIML frameworks and machine learning libraries
Compensation
- We are committed to providing fair and competitive compensation.
- The salary range for this position is $78,000 to $250,000 per year.
- This range reflects the compensation offered across the locations where we hire.
- The exact salary will be determined based on the candidate's work location, specific role, skill set, and level of expertise.
Benefits
- We offer a comprehensive benefits package, including:
Health Coverage
- Medical, dental, and vision insurance
Additional Insurance
- Basic Life/AD&D, Voluntary Life/AD&D, Short and Long-Term Disability, Accident, Critical Illness, Hospitalization Indemnity, and Pet Insurance
Retirement Plan
- 401(k) plan with company match
Paid Time Off
- Generous PTO, paid holidays, parental leave, and more
Wellness
- Access to wellness programs and mental health support
Professional Development
- Opportunities for growth, including tuition reimbursement
Additional Perks
- Flexible work arrangements, including remote work options
- Flexible Spending Accounts (FSAs)
- Employee referral programs
- Bonus opportunities
- Technology allowance
- A diverse, inclusive, and supportive workplace culture