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Weekend Machine Vision Engineer Jobs in Washington

Machine Learning Engineer

Washington, DC ยท On-site

$130K - $200K/yr

We are seeking a Machine Learning Engineer (3-5+ years of experience) to help design, build ... Computer Vision: image classification, object detection, OCR, segmentation, deepfake detection ...

Machine Learning Engineer

Washington, DC ยท On-site +1

$130K - $200K/yr

We are seeking a Machine Learning Engineer (3-5+ years of experience) to help design, build ... Computer Vision: image classification, object detection, OCR, segmentation, deepfake detection ...

We are seeking an earlycareer Machine Learning Engineer who is excited to grow rapidly by building ... Experience or demonstrated interest in Vision ML, with familiarity in common vision models and ...

Machine Learning Engineer Our clients, a rapidly growing AI-focused software development company ... S. citizenship Preferred Qualifications โ€ข Distributed training โ€ข Computer vision โ€ข LLMs or ...

Machine Learning Engineer Our clients, a rapidly growing AI-focused software development company ... S. citizenship Preferred Qualifications โ€ข Distributed training โ€ข Computer vision โ€ข LLMs or ...

Software Engineer

Gaithersburg, MD ยท On-site +1

$78K - $116K/yr

The position involves developing technical solutions that incorporate artificial intelligence (AI), machine learning (ML), computer vision, and IoT to solve complex scientific and engineering ...

Software Engineer

Gaithersburg, MD ยท On-site

$78K - $116K/yr

The position involves developing technical solutions that incorporate artificial intelligence (AI), machine learning (ML), computer vision, and IoT to solve complex scientific and engineering ...

We are seeking an early-career Machine Learning Engineer who is excited to grow rapidly by building ... Experience or demonstrated interest in Vision ML, with familiarity in common vision models and ...

Machine Learning Engineer

Mclean, VA ยท On-site

$77K - $176K/yr

Machine Learning Engineer The Opportunity: As an experienced AI and ML engineer, you know that ... Experience with deep learning, computer vision, or generative AI * Experience with data handling ...

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Weekend Machine Vision Engineer information

What is the difference between Weekend Machine Vision Engineer vs Weekend Robotics Technician?

AspectWeekend Machine Vision EngineerWeekend Robotics Technician
Required CredentialsBachelor's in Engineering, Computer Science, or related field; knowledge of image processing and programmingAssociate's or Bachelor's in Robotics, Electronics, or related field; hands-on technical skills
Work EnvironmentTech labs, manufacturing facilities, or research centers focusing on vision systemsManufacturing floors, maintenance workshops, or field service settings
Industry UsageManufacturing, automation, quality controlManufacturing, assembly lines, equipment maintenance

The Weekend Machine Vision Engineer primarily focuses on developing and implementing vision systems for automation and quality control, requiring programming and image processing skills. In contrast, the Weekend Robotics Technician handles maintenance and troubleshooting of robotic systems, emphasizing hands-on technical skills. Both roles are essential in manufacturing environments but differ in their focus and daily tasks.

What are the key skills and qualifications needed to thrive as a Weekend Machine Vision Engineer, and why are they important?

To excel as a Weekend Machine Vision Engineer, you typically need a background in computer vision, image processing, and a degree in engineering, computer science, or a related field. Familiarity with programming languages like Python or C++, experience with machine vision libraries (such as OpenCV or Halcon), and knowledge of industrial camera systems are commonly required. Strong problem-solving skills, attention to detail, and effective communication are crucial soft skills for this role. These competencies ensure the development and maintenance of reliable vision systems that support high-quality automation and manufacturing processes during critical weekend operations.

What does a Weekend Machine Vision Engineer do?

A Weekend Machine Vision Engineer is responsible for developing, testing, and maintaining computer vision systems that enable machines to interpret and process visual data. This role typically involves working weekends to support production lines or R&D projects that need ongoing monitoring and updates outside of standard business hours. Key tasks include programming vision algorithms, integrating cameras and sensors, troubleshooting system issues, and collaborating with other engineers to improve automation and quality control processes. Weekend Machine Vision Engineers are commonly found in manufacturing, robotics, and quality assurance environments that require continuous technical support.

What are some common challenges faced by a Weekend Machine Vision Engineer, and how can they be addressed?

As a Weekend Machine Vision Engineer, you may encounter challenges such as troubleshooting unexpected equipment malfunctions, adapting to rapidly changing production needs, and working with limited on-site support compared to weekday shifts. To address these, it's important to develop strong problem-solving skills, stay up-to-date with the latest software and hardware updates, and maintain clear documentation for seamless communication with weekday teams. Proactively coordinating with colleagues during shift handovers and leveraging remote support resources can also help ensure smooth operations and minimize downtime.
What are the most commonly searched types of Machine Vision Engineer jobs in Washington? The most popular types of Machine Vision Engineer jobs in Washington are:
What cities in Washington are hiring for Weekend Machine Vision Engineer jobs? Cities in Washington with the most Weekend Machine Vision Engineer job openings:

Machine Learning Engineer

10a Labs

Washington, DC โ€ข On-site

$130K - $200K/yr

Full-time

Medical, Dental, Vision, PTO

Posted 18 days ago


Job description

About 10a Labs: 10a Labs is the safety and threat-intelligence layer trusted by frontier AI labs, AI unicorns, Fortune 10 companies, and leading global technology platforms. Our adversarial red teaming, model evaluations, and intelligence collection enable engineering, safety, and security teams to stay ahead of evolving threats and deploy AI systems safely.
About the Role:
We are seeking a Machine Learning Engineer (3-5+ years of experience) to help design, build, evaluate, and deploy advanced machine learning systems across a range of safety, security, and intelligence applications.
This role spans the full ML lifecycle, from dataset development and experimentation to model training, evaluation, deployment, and monitoring. You will work both independently and collaboratively across projects involving multimodal classification systems, frontier model evaluations, model distillation research, and agentic workflows. The ideal candidate combines strong engineering fundamentals with a research mindset and enjoys tackling ambiguous, high-impact problems at the frontier of AI.
You will collaborate closely with researchers, software engineers, red teamers, and subject-matter experts to develop production-ready systems that support leading AI organizations and technology companies.
Responsibilities may include:
  • Design, train, evaluate, and deploy machine learning models across text, image, audio, and multimodal domains.
  • Develop and improve classification systems for safety, security, abuse detection, and intelligence applications.
  • Conduct experiments to benchmark, evaluate, and compare AI models, including large language models and multimodal systems.
  • Contribute to model distillation, optimization, and fine-tuning efforts to improve performance, efficiency, and deployability.
  • Design evaluation pipelines, metrics, and testing frameworks to measure model capabilities, reliability, and safety.
  • Build agentic systems and automated workflows for evaluation, red teaming, research, and large-scale experimentation.
  • Own ML projects from initial research and prototyping through production deployment and monitoring.
  • Partner with software engineers to productionize ML systems and support ongoing improvements.
  • Provide technical expertise and guidance across client engagements and internal research initiatives.

We're looking for someone who:
  • Brings curiosity, creativity, and rigor to ambiguous research and engineering problems, with a bias toward experimentation and rapid iteration;
  • Thrives in collaborative, interdisciplinary environments while also being comfortable independently driving projects to completion;
  • Communicates technical concepts clearly to both technical and non-technical audiences;
  • Is resourceful, proactive, and comfortable operating in a fast-moving startup environment.
  • Is excited about developing novel approaches that advance the state of AI safety, evaluation, and security.

Requirements:
  • 3-5+ years of professional experience building and deploying machine learning systems.
  • Strong proficiency in Python and modern machine learning frameworks such as PyTorch and/or TensorFlow
  • Experience working across multiple modalities, with expertise in one or more of:
    • Computer Vision: image classification, object detection, OCR, segmentation, deepfake detection, multimodal vision-language systems, or related areas.
    • Natural Language Processing: LLMs, text classification, information extraction, retrieval systems, speech-to-text, agentic applications, or related areas.
  • Experience training, fine-tuning, evaluating, and deploying machine learning models in production environments.
  • Experience designing evaluation methodologies, benchmarking systems, and model performance metrics.
  • Experience with MLOps tools and practices (Docker, Kubernetes, CI/CD for ML, MLflow, etc.)
  • Experience with cloud platforms such as Google Cloud Platform (preferred), AWS, or Azure, including ML infrastructure, workflow orchestration, storage, and database services.
  • Familiarity or experience with model distillation, synthetic data generation, reinforcement learning, or AI evaluation research is strongly preferred.

Preferred:
Experience working with frontier language models, multimodal foundation models, or AI safety evaluations.Prior experience in cybersecurity, trust and safety, abuse prevention, threat intelligence, or related domains.Experience with retrieval-augmented generation (RAG), AI agent frameworks, and context orchestration systems such as LangChain, LlamaIndex, OpenAI Agents, or AutoGen.
Compensation:
  • Salary Range: $130K-$200K, depending on experience and location
  • Bonus: Performance-based annual bonus
  • Professional Development: Support for conferences, continuing education, or leadership training
  • Work Environment: Fully remote, U.S.-based
  • Health Benefits: Comprehensive health, dental, and vision coverage

Time Off: Generous PTO and paid holiday schedule