AI Engineer

Job summary

This role involves defining and developing advanced AI capabilities, focusing on the integration of neuroscience and marketing. The position requires hands-on involvement in building and operating robust AI systems that enhance the platform's functionality.

Qualifications

• 2–5+ years of experience in building and deploying machine learning models in production.
• Strong proficiency in Python and experience with frameworks such as PyTorch, TensorFlow, and/or Scikit-learn.
• Proven track record in designing and deploying generative AI systems, including multi-process workflows and multi-modal systems.
• Solid understanding of MLOps practices, including Git, Docker, CI/CD pipelines, and cloud platforms (preferably GCP).
• Experience with REST APIs and familiarity with Infrastructure as Code tools like Terraform is a plus.
• Commitment to writing clean, maintainable, and well-tested code.
• Strong problem-solving abilities and comfort with ambiguity.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or equivalent practical experience.

Responsibilities

• Lead the architecture, design, and implementation of complex AI solutions for production use.
• Manage the full lifecycle of machine learning models, from data preprocessing to deployment and monitoring.
• Collaborate with Product, Engineering, and Data teams to ensure seamless integration of AI solutions into the platform.
• Mentor junior engineers and promote best practices in software engineering and MLOps.
• Continuously evaluate and prototype emerging AI techniques to maintain competitive advantage.

Skills

• Expertise in Python and machine learning frameworks.
• Experience with generative AI and MLOps.
• Strong analytical and problem-solving skills.

Education

• Bachelor’s or Master’s degree in a relevant field.

Tools

• Python, PyTorch, TensorFlow, Scikit-learn, Git, Docker, CI/CD tools, cloud platforms (GCP), REST APIs.