TO BE CONSIDERED FOR THIS POSITION YOU MUST CURRENTLY HAVE AN ACTIVE TS/SCI WITH POLYGRAPH SECURITY CLEARANCE WITH THE FEDERAL GOVERNMENT. (U.S. CITIZENSHIP REQUIRED).

Description:
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.

Seeking an AI/ML Level 1 Engineer, responsible for building, training, fine-tuning, and evaluating advanced language models. The ideal candidate will have hands-on experience with state-of-the-art machine learning techniques, specifically for natural language processing (NLP), and will also have a strong understanding of full-stack development. This person will work across the model development lifecycle and collaborate with cross-functional teams to deliver high-impact solutions.

Key Responsibilities:
• Knowledge and experience of Language models is required
o Specific experience with Marian and multi-lingual model development
• Knowledge of Computation Linguistics is a plus
• Experience with Open-Source model libraries, Deep Learning Containers (DLC), GPU technologies and optimization / tuning
• Strong Java, C, C++ programming experience
• Willingness to support occasional on-call duties is a plus
• Model Development & Training:
o Build, train, and fine-tune machine learning models, particularly language models
o Apply best practices in model training, tuning, and optimization.
o Design and implement solutions for model performance improvement.
• Evaluation & Testing:
o Conduct rigorous model evaluation, including performance analysis and benchmarking.
o Perform error analysis, debugging, and model diagnostics to ensure quality and reliability.
• Model Deployment & Integration:
o Work with cloud-based AI platforms (especially AWS Sagemaker) to deploy and scale models.
o Integrate machine learning models into production environments, ensuring seamless integration with other systems.
• Full-Stack Engineering:
o Contribute to the development and maintenance of the full stack for AI model-based applications (front-end and back-end).
o Collaborate with software engineers to build scalable and efficient deployment pipelines.
• Collaboration & Reporting:
o Work closely with data scientists, product teams, and engineers to translate business requirements into technical solutions.
o Document workflows, model design processes, and technical specifications.

Key Qualifications:
• Technical Skills:
o Strong proficiency in AI/ML frameworks such as TensorFlow, PyTorch, or Hugging Face.
o Expertise in model training, evaluation, and deployment.
o Hands-on experience with AWS tools like SageMaker, Lambda, EC2, and S3.
o Experience in developing full-stack software applications (JavaScript, Python, Java, etc.).
o Solid understanding of data structures, algorithms, and system design.
• Experience & Background:
o Extensive experience in machine learning model development, including natural language processing (NLP).
o Experience with model evaluation, optimization, and performance monitoring.
o Proven experience in software engineering with strong coding skills.
o Experience working in a government or defense-related environment is highly preferred.
• Additional Skills:
o Experience with model versioning and management using tools such as MLFlow or Git.
o Familiarity with containerization tools (i.e. Kubernetes).
o Strong problem-solving and analytical skills.
o Excellent communication and collaboration abilities.
Nice to Have:
• Experience with secure data handling and compliance requirements
• Experience working with Large Language Models (LLMs)

Polygraph must be within 7 years.
2 years experience in applied machine learning in programs and contracts of similar scope, type, and complexity is required.  A B.S. degree in advanced math (e.g., calculus, linear algebra or Bayesian statistics), computer science or related STEM discipline from an accredited college or university is required. 3 years of additional machine learning experience on projects with similar machine learning processes may be substituted for a bachelor’s degree.

Compensation:
We are committed to providing fair and competitive compensation. The salary range for our positions vary depending on accepted contractual position skill level. These salaries fall within the range of $78,000 to $275,000 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