NLP Engineer Israel

NLP Engineer Israel

We, one of Israel’s most valued private software companies, are at the forefront of integrating AI and machine learning into customer-facing roles. Our solution is trusted by over 4,000 innovative companies, including PayPal, Twilio, Shopify, Hubspot, and LinkedIn, to automate and enhance sales professional activities. We’re looking for a Machine Learning Engineer to join our NLP team for a six-month temporary position, playing a crucial role in modeling state-of-the-art AI solutions and bringing them to production.

In this role, you’ll be diving into the world of NLP, developing data pipelines, and implementing machine learning models into production systems. You’ll collaborate closely with engineering, DevOps, and security teams to build robust testing infrastructure and create utility code that enhances our project capabilities. This position is not just about coding; it’s about pushing the boundaries of what’s possible in AI and machine learning.

You will:

• Develop and maintain data pipelines for advanced machine learning models.
• Implement these models in production, ensuring efficiency and scalability.
• Collaborate with cross-functional teams, including engineering, DevOps, and security, to enhance model deployment and performance.
• Create and manage utility code for consistent use across projects.
• Contribute to model-serving solutions and continuously improve our AI capabilities.

You are:

• A team player who thrives in collaborative environments.
• Passionate about AI, machine learning, and technology innovation.
• Proactive in sharing knowledge and code with team members.
• Eager to work in a dynamic, fast-paced setting.

You have:

• At least 3 years of experience in a similar machine learning or engineering role.
• Proficiency in Python, Git, Jenkins, and working with databases.
• Familiarity with machine learning libraries such as Torch, Pandas, and NumPy.
• Experience or knowledge of model-serving libraries like KServe, Triton, TensorRT (a plus).
• A solid understanding of machine learning concepts (formal education in ML is not required).