Software Engineer II in Herndon, Virginia at Quevera LLC

Job Description:

Quevera is seeking a Software Engineer II to join our team. At Quevera, we don’t just offer jobs—we provide opportunities to be part of a dynamic, forward-thinking community that fosters innovation, collaboration, and personal growth. You’ll work with industry experts, take on exciting challenges, and have the creative freedom to build cutting-edge solutions, all while advancing your career in a space that truly values your skills and ideas.

HIGHLIGHT'S OF WORKING FOR QUEVERA:

Quevera employees voted Quevera as a TOP EMPLOYER in the Baltimore /DC area by the Washington for 2025 for the 5th consecutive year!

Excellent Quevera's Benefits:

Medical/Dental/Vision (100% Employer Paid Medical Plan)

Short/Long Term Disability (Employer Paid)

Life Insurance (Employer Paid)

Yearly $5,000 towards education/training/certification.

Employees are in control of their career path through our Career Pathway Program.

Employer paid Company Vacation Package for you and a guest!

Retirement:

Quevera will match up to 6% towards your 401K and an additional 4% profit sharing!

REQUIRED - MUST have a current TS/SCI Polygraph clearance to apply for role. Only those with a current TS/SCI with Poly clearance will be considered.

Duties and Responsibilities:

• Design and execute fine-tuning pipelines for Vision-Language Models (VLMs) on domain-specific imagery datasets, including data preprocessing, training orchestration, and hyperparameter optimization
• Develop and implement evaluation frameworks for multimodal model performance, including task-specific metrics for image understanding, visual question answering, and spatial reasoning
• Build scalable training infrastructure on AWS (SageMaker, EC2 GPU instances) for distributed fine-tuning of large multimodal models
  Engineer data pipelines for curating, annotating, and transforming geospatial imagery datasets into model-ready formats for supervised and instruction-tuning workflows
• Collaborate with applied scientists and solutions architects to iterate on model architectures, adapter strategies (LoRA/QLoRA), and inference optimization techniques

Required Experience:

• TS/SCI with CI Poly required with current NGA eligibility and SBU/SECNet/COE accounts
• Must be willing to work in SCIF daily or as needed
• 5+ years of professional machine learning engineering experience with a focus on deep learning
• 1+ years of hands-on experience fine-tuning large foundation models (LLMs or VLMs)
• Experience with parameter-efficient fine-tuning methods (LoRA, QLoRA, adapters)
• Familiarity with supervised fine-tuning, instruction tuning, and RLHF/DPO alignment techniques
• 4+ years of advanced Python development for ML workloads
• Strong proficiency with PyTorch and the HuggingFace ecosystem (Transformers, PEFT, Datasets, Accelerate)
• Experience with distributed training frameworks (DeepSpeed, FSDP, or Megatron)
• 3+ years of experience with computer vision or multimodal models
• Understanding of vision transformer architectures (ViT, CLIP, LLaVA-family models, or similar)
• Experience processing and augmenting image datasets at scale
• 3+ years of experience with AWS ML infrastructure
  SageMaker Training jobs, Processing jobs, and endpoint deployment
  GPU instance selection, multi-node training, and cost optimization on EC2 (P4/P5/G5/G6e)
  S3 data management for large-scale training datasets
• 2+ years of experience building ML evaluation pipelines
  Automated benchmarking, metric computation, and result analysis
  Experience with both quantitative metrics and qualitative/human evaluation approaches
• Strong software engineering fundamentals (version control, testing, CI/CD for ML workflows)

Desired Experience:

• 2+ years of experience with geospatial or remote sensing imagery
  Familiarity with electro-optical and SAR satellite imagery formats and characteristics
  Understanding of geospatial metadata, coordinate systems, and imagery preprocessing
• Experience with model quantization and inference optimization (vLLM, TensorRT, ONNX)
  Experience with MLOps and experiment tracking tools (MLflow, Weights & Biases, SageMaker Experiments)
  Familiarity with data annotation platforms and active learning workflows for imagery
  Experience with containerized ML workflows (Docker, ECR, ECS/EKS)
  2+ years of experience with Authority to Operate (ATO) processes in government environments
  Implementation of NIST 800-53 controls and security compliance for ML systems
• Experience deploying models in air-gapped or disconnected environments
  Familiarity with multimodal evaluation benchmarks (MMMU, MMBench, GQA, or domain-specific equivalents)
  Publications or demonstrated contributions in computer vision, VLMs, or multimodal AI
  Experience with synthetic data generation for training data augmentation
  Complete items below line after a partner is selected

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