About the Role

We're looking for an AI Engineer with a strong foundation in machine learning and practical experience building AI-powered solutions. In this role, you'll work on real-world projects, help train and deploy models, and collaborate with data scientists and software engineers to bring AI features into our products. You should be comfortable taking a project from idea to production, with guidance from senior team members.

What You’ll Do

• Dataset Creation and Preparation: Contribute directly to dataset construction by performing hands-on data sourcing,cleaning, preprocessing, and implementing data augmentation strategies to build high-quality, robust training sets.
• Model Development & Fine-Tuning: Build, train, and fine-tune large multimodal models (e.g., Gemma, Mistral, Llama) using the prepared datasets to perform complex analysis and classification.
• Agentic AI Implementation: Develop and implement sophisticated AI agents and agentic workflows using frameworks like LangGraph. You will write the code that enables multi-step reasoning and dynamic tool use within our system.
• API & Infrastructure: Develop, test, and deploy a secure, high-performance RESTful API (using FastAPI or a similar framework). You will also containerize the application with Docker for efficient deployment.
• Cloud Deployment & MLOps: Manage the deployment process of the containerized application to Google Cloud Run. 
• Evaluation & Optimization: Implement and run evaluation scripts to measure model accuracy and agent task success against predefined targets.
• Collaboration: Collaborate with software engineers to integrate models into production systems

What We’re Looking For

• Proven Experience: A strong track record and hands-on experience building and deploying machine learning models in a production environment.
• Data Handling: Practical experience with data-centric AI development, including dataset cleaning, preprocessing, and augmentation techniques.
• Deep Learning Expertise: Experience working with or fine-tuning large multimodal models that process both image and text data.
• AI Agent Development: Hands-on experience building AI agents and/or implementing agentic workflows using modern frameworks such as LangGraph, LangChain, or similar technologies.
• Software Engineering: Strong programming skills in Python and Typescript. Proven ability to develop RESTful APIs and containerize applications with Docker.
• Cloud Proficiency: Experience deploying applications on a major cloud platform (GCP, AWS, or Azure).



• Database Proficiency: Experience with both SQL and NoSQL databases (e.g., PostgreSQL, Firestore, MongoDB).

Agile Methodologies: Experience working within an Agile/Scrum framework and using project management tools like JIRA.