Machine Learning Researcher

About Visual Layer

Visual Layer is a rapidly growing startup focused on leveraging proprietary algorithms to unlock the full potential of your visual data. We are building a single access layer for all visual data that allows users to seamlessly explore, enrich, and manage vast amounts of unstructured images and videos with ease. Visual Layer's solution leverages a proprietary graph engine that allows performing graph analytics & graph search on very large scale data. Our innovative solutions empower businesses across various industries to harness the power of visual data. Visual Layer is backed by top-tier US VCs Madrona & Insights Partners and has offices in Tel Aviv and Stanford.

About the Role

As an ML Researcher, you’ll be at the forefront of pushing the boundaries of machine learning and computer vision at scale. This role is ideal for someone passionate about research and prototyping, who thrives on applying state-of-the-art ML techniques to large-scale, real-world visual data problems.

You’ll collaborate closely with our ML Engineers, Product Engineers, and leadership to explore novel approaches, prototype algorithms, and help shape the future of Visual Layer’s core ML stack. Your work will directly impact the intelligence and capabilities of our platform across use cases in surveillance, enterprise search, synthetic data analysis, and more.

Your Impact & Responsibilities

• Lead end-to-end development research efforts in large-scale computer vision, visual representation learning, and multimodal AI.
• Develop, prototype, and benchmark novel ML models — including foundation models, and multi-modal models such as VLMs.
• Collaborate with engineering teams to transition research into scalable, production-ready systems.
• Stay current with state-of-the-art literature, and identify opportunities to apply recent advances to our product.
• Contribute to open-source and academic publications where appropriate.

Desired Experience & Skills

• Advanced degree (Ph.D. or M.Sc.) in a quantitative, computing, or engineering field, with a strong research background in ML or CV.
• Deep understanding of modern ML techniques, including Transformers, generative models (e.g., diffusion models, VLMs), and representation learning.
• Hands-on experience with PyTorch, TensorFlow, or JAX, and familiarity with ML tooling such as HuggingFace, Lightning, or ONNX.
• Experience working with large-scale visual datasets and training models at scale.
• Strong publication record or demonstrated ability to translate research into working systems.

Nice to Have

• Experience with multi-modal learning (e.g., vision-language models, CLIP, BLIP).
• Strong coding skills in C++ for custom ops or model optimization.