SignalPET is a technology and AI leader in the veterinary field. Using state-of-the-art machine learning techniques and patented technology, SignalPET assists veterinarians in diagnosing and treating companion animals worldwide.

Responsibilities

As part of the ML engineering team, you will:

• Build and maintain the infrastructure of the core model training and inference flows, which are a critical part of the main company products.
• Take a key part in the incorporation of AI agentic tools into the team’s development cycle, and provide suggestions for our model training flows.
• Lead the design and implementation of a robust architecture for our internal ML ops system that manages the lifecycle of over 100 production-grade vision models. Coordinate with the group members and relevant stakeholders.
• Work on and install automated monitoring for production data flows that involve both vision models and LLMs.
• Conclude deep business data analyses over the unparalleled and rich veterinary dataset of the company (processed data of over 4 million radiologist images).
• Work on cloud-based (AWS) solutions, in a full GitOps setup.
• Operate autonomously in the group, design and plan your own tasks, while communicating clear status and key decisions made.

Requirements

• At least 4 years of hands-on experience in ML engineering/Backend development of large-scale services.
• Experience with industry-standard classic ML and LLM frameworks, Deep knowledge of AWS solutions (SageMaker, etc.), and maintenance of large-scale production services - an advantage.
• Proficiency in Python, TypeScript, PHP, and development in a containerized environment.

Attributes

• Team player: Collaborate with others, clearly communicate your results, align your work with the team's goals, and maintain your self-sufficiency.
• Problem-solving skills: Ability to identify problems, evaluate alternatives, and implement effective solutions.
• Adaptability: Openness to learning new techniques, adapting to changing requirements, and embracing new technologies.
• Initiative: Proactive in taking on new challenges, seeking out opportunities to improve processes, and driving results.
• First principle thinker.