Senior AI/ML Engineer

Responsibilities

• Enhance our retrieval-augmented generation (RAG) capabilities, ensuring our models effectively integrate and utilize diverse data sources.
• Work on embedding generation techniques, optimizing them for accuracy and efficiency.
• Keep abreast of the latest developments in AI models, their evolving capabilities, and the complexities of integration.
• Position yourself as the go-to expert within the team, guiding our end users in crafting their use cases with the most suitable models.
• Collaborate with backend and frontend teams to integrate AI models into products and services.
• We're all about our users - listen to their needs, help them, build strong relationships!
• Expect to dive into customer support now and then as everyone else in the team.

Requirements

• Bachelor's or Master's degree in Computer Science, Machine Learning, AI, or related fields.
• Proven experience in machine learning and AI, with a focus on generative models.
• Knowledge of retrieval-augmented generation pipelines and their implementation.
• Strong proficiency in Python and popular machine learning frameworks like TensorFlow or PyTorch.
• Experience with embedding techniques and understanding of their applications in AI models.
• Excellent problem-solving skills and the ability to work in fast-paced environments.
• Strong communication and collaboration skills.

Qualifications

• You will be a great fit if you have...
• Bachelor's or Master's degree in Computer Science, Machine Learning, AI, or related fields.
• Proven experience in machine learning and AI, with a focus on generative models.
• Knowledge of retrieval-augmented generation pipelines and their implementation.
• Strong proficiency in Python and popular machine learning frameworks like TensorFlow or PyTorch.
• Experience with embedding techniques and understanding of their applications in AI models.
• Excellent problem-solving skills and the ability to work in fast-paced environments.
• Strong communication and collaboration skills.

Preferred Qualifications

• You will be an exceptional fit if you also have...
• PhD in a relevant field.
• Published research or projects in the field of generative AI, embeddings, or retrieval-augmented generation.
• Experience with large-scale ML deployments in a production environment.
• Contribution to open-source AI/ML projects.
• In-depth knowledge of generative AI hardware, including an understanding of GPU architectures, requirements, and optimization techniques for AI model deployment.