Software Engineer II

Quevera LLC
Herndon, United States of America
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Junior

Job location

Herndon, United States of America

Tech stack

Training Data
Artificial Intelligence
Amazon Web Services (AWS)
Amazon Web Services (AWS)
Amazon Web Services (AWS)
Computer Vision
Continuous Integration
Data Cleansing
Distributed Computing Environment
Machine Learning
Language Modeling
PyTorch
Large Language Models
Deep Learning
Question Answering
Optimization Algorithms
ONNX (Open Neural Network Exchange) Format
HuggingFace
Data Management
Machine Learning Operations
TensorRT
Software Version Control
Data Pipelines
Docker
Data Generation

Job description

  • 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

Requirements

Do you have experience in Version control systems?, * 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

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

About the company

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.

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