Computer Vision & ML Expert

Not recently verified

Tel Aviv-Yafo, Tel Aviv District, Israel

✓ Not duplicate

Sign Up to Apply › Fit & Gaps

SaveNot Relevant

Match score

See how well you match this role, and what's worth sharpening before you apply.

Sign Up to Check Your Fit

Trevo

Is this role relevant for you?

Job Description

About the role

Computer Vision & ML Expert (AI Training) What if your expertise in computer vision could directly shape how the next generation of AI systems perceives, interprets, and understands the visual world? We're looking for Computer Vision & Machine Learning Experts based in Tel Aviv and across Israel to evaluate, improve, and guide AI models that process images, video, and visual data — helping build systems that truly see. Israel's deep tech ecosystem is a global leader in computer vision — from autonomous driving and medical imaging to defense and consumer AI. Whether you're a researcher, startup engineer, or advanced graduate student, your technical depth will have a direct, measurable impact on AI systems used by millions. • Organization: Alignerr • Type: Hourly Contract • Location: Remote • Commitment: 10–40 hours/week

What you'll do

Evaluate AI-generated outputs related to image recognition, object detection, segmentation, and visual reasoning tasks
Assess the quality, accuracy, and robustness of computer vision model predictions and outputs
Identify failure modes, edge cases, and biases in visual AI systems

Alignerr

Full Company Profile ›

Start Free›

Get Data & AI jobs on Telegram

New roles selected from the catalog in your field, on your phone.

Join channel

Create, review, and refine training data annotations for computer vision pipelines

Provide expert-level feedback on model behavior, architecture decisions, and output quality

Write detailed technical evaluations and suggest concrete improvements

Work across diverse visual domains — from natural images and medical imaging to autonomous systems and document understanding

Complete task-based assignments independently on your own schedule

Requirements

Strong foundational knowledge of computer vision — object detection, image classification, semantic segmentation, pose estimation, or related areas
Hands-on experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX
Familiarity with common CV architectures (CNNs, Vision Transformers, diffusion models, etc.)
Comfortable reading and understanding ML research papers
Solid understanding of data preprocessing, augmentation, and annotation best practices for visual data
Detail-oriented and systematic in evaluating model outputs
Clear, concise written communicator who can explain technical concepts effectively
Self-motivated and reliable when working independently

Nice to have

MS or PhD in Computer Science, Electrical Engineering, or a related field with a focus on computer vision or machine learning
Published research in top CV/ML venues (CVPR, ICCV, ECCV, NeurIPS, ICML, etc.)
Experience with 3D vision, video understanding, generative models, or multimodal AI
Familiarity with MLOps tools, experiment tracking, and model evaluation pipelines
Background in specialized domains such as medical imaging, remote sensing, robotics, or autonomous driving
Experience with annotation platforms and data quality workflows at scale
Proficiency in Python and scientific computing libraries (NumPy, OpenCV, scikit-learn)
Why Join Us
Work on cutting-edge AI projects alongside leading research labs
Fully remote and flexible — work when and where it suits you
Freelance autonomy with the structure of meaningful, task-based work
Make a direct, tangible impact on how AI systems perceive and interpret the visual world
Engage with diverse, challenging problems across multiple visual domains
Potential for ongoing work and contract extension as new projects launch
Join a global community of top-tier AI practitioners shaping the future of machine intelligence

Tech stack

Computer VisionPythonTensorFlowPyTorchscikit-learnNumPy

🍪 Usage-analytics transparency

About the role

What you'll do

Requirements

Nice to have

Tech stack