Job Description:Quevera is seeking a highly skilled
Software Engineer II with an
active TS/SCI clearance with Polygraph to support mission-critical programs. In this role, you will develop and optimize advanced machine learning solutions supporting multimodal artificial intelligence and computer vision applications for national security missions.
Working alongside applied scientists and engineering teams, you will design scalable machine learning pipelines, fine-tune Vision-Language Models (VLMs), build AWS-based training infrastructure, and develop data processing and evaluation frameworks for large-scale geospatial imagery datasets. You'll leverage modern AI technologies to deliver high-performing, secure, and production-ready machine learning solutions.
As a Software Engineer II, you'll have the opportunity to work with cutting-edge AI technologies, collaborate with industry experts, and contribute to innovative solutions supporting critical national security missions.
Work Schedule:Work Location: Must be willing to work onsite in a SCIF daily, or as required.
Job Responsibilities:- Design and execute fine-tuning pipelines for Vision-Language Models (VLMs) using domain-specific imagery datasets.
- Develop data preprocessing, training orchestration, and hyperparameter optimization workflows.
- Build and implement evaluation frameworks for multimodal model performance, including image understanding, visual question answering, and spatial reasoning.
- Develop scalable distributed training infrastructure using AWS services, including SageMaker and EC2 GPU instances.
- Engineer data pipelines for curating, annotating, and transforming geospatial imagery into model-ready datasets.
- Collaborate with applied scientists and solutions architects to optimize model architectures and parameter-efficient fine-tuning strategies, including LoRA and QLoRA.
- Optimize model inference performance and deployment workflows.
- Develop secure, scalable machine learning solutions that support mission requirements.
Minimum Requirements:- Active TS/SCI clearance with Polygraph required.
- Current NGA eligibility with active SBU, SECNet, and COE accounts.
- Five (5) or more years of professional machine learning engineering experience with a focus on deep learning.
- One (1) or more years of experience fine-tuning large language models (LLMs) or Vision-Language Models (VLMs).
- Experience with parameter-efficient fine-tuning techniques, including LoRA, QLoRA, and adapters.
- Familiarity with supervised fine-tuning, instruction tuning, and RLHF/DPO alignment techniques.
- Four (4) or more years of advanced Python development for machine learning workloads.
- Strong proficiency with PyTorch and the Hugging Face ecosystem, including Transformers, PEFT, Datasets, and Accelerate.
- Experience with distributed training frameworks such as DeepSpeed, FSDP, or Megatron.
- Three (3) or more years of experience with computer vision or multimodal AI models.
- Understanding of Vision Transformer architectures, including ViT, CLIP, LLaVA, or similar models.
- Experience processing and augmenting image datasets at scale.
- Three (3) or more years of experience with AWS machine learning infrastructure, including SageMaker, EC2 GPU instances, and Amazon S3.
- Experience building machine learning evaluation pipelines, including automated benchmarking, metric computation, and result analysis.
- Strong software engineering fundamentals, including version control, testing, and CI/CD practices for machine learning workflows.
Desired Skills:- Active TS/SCI clearance with Polygraph required.
- Current NGA eligibility with active SBU, SECNet, and COE accounts.
- Five (5) or more years of professional machine learning engineering experience with a focus on deep learning.
- One (1) or more years of experience fine-tuning large language models (LLMs) or Vision-Language Models (VLMs).
- Experience with parameter-efficient fine-tuning techniques, including LoRA, QLoRA, and adapters.
- Familiarity with supervised fine-tuning, instruction tuning, and RLHF/DPO alignment techniques.
- Four (4) or more years of advanced Python development for machine learning workloads.
- Strong proficiency with PyTorch and the Hugging Face ecosystem, including Transformers, PEFT, Datasets, and Accelerate.
- Experience with distributed training frameworks such as DeepSpeed, FSDP, or Megatron.
- Three (3) or more years of experience with computer vision or multimodal AI models.
- Understanding of Vision Transformer architectures, including ViT, CLIP, LLaVA, or similar models.
- Experience processing and augmenting image datasets at scale.
- Three (3) or more years of experience with AWS machine learning infrastructure, including SageMaker, EC2 GPU instances, and Amazon S3.
- Experience building machine learning evaluation pipelines, including automated benchmarking, metric computation, and result analysis.
- Strong software engineering fundamentals, including version control, testing, and CI/CD practices for machine learning workflows.
Why Join Quevera?Award-Winning CultureQuevera was recognized as a
Top Workplace in the Washington, DC/Baltimore region for 2025, marking our
fifth consecutive year receiving this distinction based on employee feedback.
Outstanding Benefits- We invest in our employees and their families through a highly competitive benefits package, including:
- 100% employer-paid medical coverage (optional plan)
- Competitive options for Medical, Dental and Vision insurance
- Employer-paid short-term and long-term disability coverage
- Employer-paid life insurance
- $5,000 annually for education, training, certifications, and professional development
- Career advancement through our structured IQWay Program
- Up to 6% 401(k) match
- Additional 4% profit-sharing contribution
At Quevera, we believe exceptional people deserve exceptional opportunities. We're more than just a workplace-we're a team of innovators, problem-solvers, and industry experts committed to delivering mission-critical solutions while fostering professional growth, collaboration, and technical excellence.
Quevera is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected veteran status, age or any other characteristic protected by law. #LI-AA1
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