Enterprise - Senior AI/ML Engineer - Python, Java, AWS

Erias Ventures•Annapolis Junction, MD

About The Position

Erias Ventures is seeking a Senior AI/ML Engineer to build, train, fine-tune, and evaluate advanced language models, with a particular focus on natural language processing. The engineer will work across the model development lifecycle and collaborate with cross-functional teams to deliver solutions, while also contributing to the full-stack development of AI model-based applications. The role includes selecting appropriate datasets, performing statistical analysis, running machine-learning algorithms, and using results to improve models. The engineer will apply model-training and optimization best practices, conduct benchmarking and error analysis, debug models, and support deployment and integration into production. The position works with cloud-based AI platforms, especially AWS SageMaker, and includes building scalable deployment pipelines and documenting workflows, model designs, and technical specifications. A current Top-Secret/SCI clearance with polygraph, obtained within the past seven years, is required. Candidates cannot be sponsored or nominated for a government security clearance for this position. Two years of applied machine-learning experience on programs and contracts of similar scope, type, and complexity is required. A bachelor’s degree in advanced mathematics, computer science, or a related STEM discipline is required; three additional years of comparable machine-learning experience may substitute for the degree. The expected salary range is $175,000–$195,000, depending on education and years of experience. Erias Ventures describes its culture as entrepreneurial and focused on creative problem-solving, open communication, employee empowerment, and a diverse range of technical perspectives.

Requirements

A current Top-Secret/SCI security clearance with polygraph, obtained within the past seven years; clearance sponsorship or nomination is not available for this position.
At least two years of applied machine-learning experience on programs and contracts of similar scope, type, and complexity.
A bachelor’s degree in advanced mathematics, computer science, or a related STEM discipline from an accredited college or university; three additional years of comparable machine-learning experience may substitute for the degree.
Knowledge of and experience with language models.
Specific experience with Marian and multilingual model development.
Experience with open-source model libraries, Deep Learning Containers, GPU technologies, and optimization or tuning.
Strong Java, C, and C++ programming experience.
Strong proficiency with AI/ML frameworks such as TensorFlow, PyTorch, or Hugging Face.
Expertise in model training, evaluation, and deployment.
Hands-on experience with AWS tools such as SageMaker, Lambda, EC2, and S3.
Experience developing full-stack software applications using technologies such as JavaScript, Python, and Java.
Solid understanding of data structures, algorithms, and system design.
Extensive machine-learning model development experience, including natural language processing.
Experience with model evaluation, optimization, and performance monitoring.
Proven software engineering experience and strong coding skills.
Experience with model versioning and management tools such as MLflow or Git.
Familiarity with containerization tools such as Kubernetes.
Strong problem-solving and analytical skills.
Excellent communication and collaboration abilities.

Nice To Haves

Experience working in a government or defense-related environment.
Knowledge of computational linguistics.
Willingness to support occasional on-call duties.
Experience with secure data handling and compliance requirements.
Experience working with large language models.

Responsibilities

Select appropriate datasets and perform statistical analysis.
Run machine-learning algorithms and use results to improve models.
Build, train, and fine-tune machine-learning models, particularly language models.
Apply best practices in model training, tuning, and optimization.
Design and implement solutions to improve model performance.
Conduct model evaluation, performance analysis, and benchmarking.
Perform error analysis, debugging, and model diagnostics to support quality and reliability.
Deploy and scale models using cloud-based AI platforms, especially AWS SageMaker.
Integrate machine-learning models into production environments and oversee system integration.
Contribute to the front-end and back-end development and maintenance of AI model-based applications.
Collaborate with software engineers to build scalable, efficient deployment pipelines.
Work with data scientists, product teams, and engineers to translate business requirements into technical solutions.
Document workflows, model design processes, and technical specifications.
Train and retrain systems when needed and run standard testing and evaluation protocols.

Benefits

Above-market hourly pay.
11% Roth or Traditional 401(k) contribution with immediate vesting and deposit.
Spot bonuses for assisting with business development and company growth.
Professional development bonuses for certificates and degrees.
Company-subsidized medical coverage.
Company-paid vision and dental coverage.
Company-paid long-term disability, short-term disability, and group life insurance.
Monthly wellness reimbursement.
Paid time off, flexible work schedules, and a birthday off.
Amazon Prime membership and monthly internet reimbursement.
Technology and productivity allowance for equipment and supplies.
Morale-building and company events.
Onboarding and annual swag.
Company-paid professional development and training.