ZipRecruiter

Log In

2

Remote Rlhf Jobs in Washington (NOW HIRING)

aqua IT

AI/ML Engineer (Computer Vision)

Herndon, VA · On-site +1

Familiarity with supervised fine-tuning, instruction tuning, and RLHF/DPO alignment techniques * 4+ ... remote sensing imagery * Familiarity with electro-optical and SAR satellite imagery formats and ...

People also search for

All JobsRlhf JobsRemote Rlhf JobsRemote Rlhf Jobs in Washington

Remote Rlhf information

What are the key skills and qualifications needed to thrive as a Remote RLHF (Reinforcement Learning from Human Feedback) Engineer, and why are they important?

To succeed as a Remote RLHF Engineer, you need expertise in machine learning, reinforcement learning, and programming languages like Python, often supported by an advanced degree in computer science or related fields. Familiarity with ML frameworks (such as TensorFlow or PyTorch), version control systems, and cloud computing platforms is typically required. Strong problem-solving, communication, and self-management skills are vital for remote collaboration and interpreting human feedback effectively. These skills enable the development of robust AI systems that can learn efficiently from human input while ensuring productive teamwork in a distributed environment.

How does a Remote RLHF (Reinforcement Learning from Human Feedback) specialist typically collaborate with other team members?

A Remote RLHF specialist often works closely with data scientists, machine learning engineers, and product managers to design and refine AI models using human feedback. Collaboration usually happens through regular virtual meetings, cloud-based code repositories, and shared annotation tools. The role requires clear communication to ensure that human feedback is accurately integrated into the learning process and that model improvements align with project goals. Being proactive in sharing findings and challenges is key, as team members may be distributed across different time zones.

What is a Remote RLHF job?

A Remote RLHF (Reinforcement Learning from Human Feedback) job involves working with artificial intelligence systems, particularly large language models, to improve their performance using feedback from humans. In this role, individuals may annotate data, provide quality evaluations, or help design feedback mechanisms while working from a remote location. These jobs are crucial for ensuring AI models align better with human values and expectations, and they are often offered by AI research companies or organizations focused on machine learning. The work can involve tasks such as ranking AI-generated responses, identifying errors, and suggesting improvements. Remote RLHF positions are popular due to their flexibility and the opportunity to contribute to cutting-edge AI technology.

What is the difference between Remote Rlhf vs Remote Rlhf?

AspectRemote RlhfRemote Rlhf
CredentialsTypically requires certification in mental health or counseling, such as LPC or LCSWSimilar credentials, often with additional training in specific therapy methods
Work EnvironmentRemote, client-facing sessions via telehealth platformsRemote, providing therapy or support services online
Industry UsageCommon in mental health, therapy, and counseling sectorsUsed in mental health and support services, often interchangeably with Rlhf

Remote Rlhf and Remote Rlhf are similar roles in mental health support, primarily differing in specific certifications or training focus. Both roles involve providing remote therapy or support services via telehealth platforms, making them highly comparable in work environment and industry usage.

What are the most commonly searched types of Rlhf jobs in Washington? The most popular types of Rlhf jobs in Washington are:
What are popular job titles related to Remote Rlhf jobs in Washington? For Remote Rlhf jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Remote Rlhf jobs in Washington look for? The top searched job categories for Remote Rlhf jobs in Washington are:
What cities in Washington are hiring for Remote Rlhf jobs? Cities in Washington with the most Remote Rlhf job openings:
Remote Rlhf jobs near you

AI/ML Engineer (Computer Vision)

aqua IT

Herndon, VA • On-site, Remote

Full-time

Posted 4 days ago

Job description

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

Basic Requirements

  • TS/SCI with CI Poly required
  • 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)

Preferred Qualifications:

  • 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