Software Engineer II
Role details
Job location
Tech stack
Job description
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Design and execute fine-tuning pipelines for Vision-Language Models (VLMs) on domain-specific imagery datasets, including data preprocessing, training orchestration, and hyperparameter optimization
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Develop and implement evaluation frameworks for multimodal model performance, including task-specific metrics for image understanding, visual question answering, and spatial reasoning
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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
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Collaborate with applied scientists and solutions architects to iterate on model architectures, adapter strategies (LoRA/QLoRA), and inference optimization techniques
Requirements
Do you have experience in Version control systems?, * TS/SCI with CI Poly required with current NGA eligibility and SBU/SECNet/COE accounts
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Must be willing to work in SCIF daily or as needed
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5+ years of professional machine learning engineering experience with a focus on deep learning
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1+ years of hands-on experience fine-tuning large foundation models (LLMs or VLMs)
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Experience with parameter-efficient fine-tuning methods (LoRA, QLoRA, adapters)
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Familiarity with supervised fine-tuning, instruction tuning, and RLHF/DPO alignment techniques
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4+ years of advanced Python development for ML workloads
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Strong proficiency with PyTorch and the HuggingFace ecosystem (Transformers, PEFT, Datasets, Accelerate)
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Experience with distributed training frameworks (DeepSpeed, FSDP, or Megatron)
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3+ years of experience with computer vision or multimodal models
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Understanding of vision transformer architectures (ViT, CLIP, LLaVA-family models, or similar)
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Experience processing and augmenting image datasets at scale
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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
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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
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Strong software engineering fundamentals (version control, testing, CI/CD for ML workflows)
Desired Experience:
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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
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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
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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
Benefits & conditions
Pulled from the full job description
- 401(k) 4% Match
- 401(k) matching
- Vision insurance
- Dental insurance
- Life insurance
- Disability insurance
- Profit sharing, 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