Machine Learning Engineer

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.

What we are looking for

We are seeking a talented and experienced ML Engineer to join our Algorithmic Research Team. The ideal candidate is a quick learner with the ability to independently solve complex problems. As an ML Engineer, you will collaborate with ML Researchers, Software Engineers, and other stakeholders to develop and maintain our machine learning infrastructure. Your role will be pivotal in optimizing our systems for performance and scalability, ensuring that our products are efficient and reliable.

Your Impact & Responsibilities

• Build and maintain scalable inference pipelines powering Visual Layer’s core capabilities, utilizing best coding practices to ensure efficient and memory-safe runtimes.
• Develop and maintain ML infrastructure to support model development, training, and deployment. Collaborate with ML Researchers to integrate machine learning models into production systems.
• Contribute to the optimization and scalability of our proprietary graph engine.
• Participate in code reviews and provide constructive feedback.
• Write production-grade code and directly contribute to product offerings.

Your Knowledge & Skills

• Demonstrated experience maintaining large-scale production systems.
• Strong programming skills with deep understanding of coding best practices.
• Extensive experience with machine learning frameworks such as PyTorch, TensorFlow, ONNX, Transformers, etc.
• Experience with ML operations, model deployment, and infrastructure management.
• Proven ability to optimize code for performance and memory efficiency.
• Nice to have:
• Experience working with large-scale distributed systems.
• Familiarity with C/C++