over 1 year ago
Columbia, MD, USASenior
Base Salary
$205k - $270k/yr
Responsibilities
- Deploy machine-learning models and LLMs in secure, air-gapped customer environments.
- Manage the end-to-end model lifecycle in AWS.
- Build scalable, production-ready and secure data and ML pipelines.
- Perform data preprocessing and pipeline automation.
- Troubleshoot complex technical issues and collaborate with cross-functional teams.
- Support cutting-edge AI/ML engineering for federal missions.
Requirements
- Bachelor’s degree in Computer Science, Information Technology, or a related field.
- At least 5 years of software engineering experience.
- Heavy data science, AI, and LLM experience.
- Experience with AWS SageMaker, Bedrock, and related services.
- Advanced Python and machine-learning framework skills, including PyTorch and TensorFlow.
- Experience deploying LLMs in secure, air-gapped environments.
- Experience with secure data preprocessing and pipeline automation.
- Proficiency with cloud platforms such as AWS, Azure, Oracle, or Google Cloud.
- TS/SCI security clearance with polygraph.
- AWS Solutions Architect Associate certification or similar certification.
- Strong problem-solving, communication, and collaboration skills.
- Familiarity with AWS GovCloud or C2S infrastructure is valued.
- Understanding of distributed systems is valued.
Benefits
- Competitive base salary of $205,000–$270,000.
- Up to 10% in 401(k) contributions with immediate vesting.
- Up to 25 days of personal time off and 11 paid floating holidays.
- Employer-paid employee health, dental, vision, life, and disability insurance premiums, with the majority of family premiums covered.
- Up to $5,250 per year for education, training, certifications, and professional memberships.
- Up to $300 per year for company-branded merchandise.
- Access to a fully equipped gym and company and team events.
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