Senior Backend AI Engineer

PropertyRadar.com•Truckee, CA

18h

About The Position

We are seeking an exceptional Senior Backend AI Engineer to join our cutting-edge AI team. In this pivotal role, you will be at the forefront of developing advanced AI-powered tools and GenAI solutions. Your expertise in machine learning, artificial intelligence, and data engineering will be instrumental in driving innovation and pushing the boundaries of what's possible in the realm of AI. At PropertyRadar, we are on a mission to provide small businesses with better access to the opportunities found in public records through a data-driven approach. We’ve been doing it for real estate investors, Realtors, mortgage brokers, home service companies, and others since 2007. About You You have AI and ML Expertise: You have a deep understanding of artificial intelligence and machine learning concepts, with extensive experience in developing and deploying AI models and algorithms. You are proficient in Python: You possess strong programming skills in Python, with the ability to write clean, efficient, and scalable code. You have Foundational Model Experience: You have hands-on experience working with foundational models such as RAG (Retrieval-Augmented Generation), and you are well-versed in their applications and limitations. You are proficient in API Building: You have experience building and designing APIs using frameworks like Flask, ensuring seamless integration and interaction between different systems and components. You are proficient in AWS tools: You are proficient in utilizing AWS services and tools for data storage, processing, and deployment of AI models. You are proficient in Big Data: You have expertise in large-scale data processing and analysis, and you are comfortable working with big data technologies. You have Vector and Embedded Vector Knowledge: You have a solid understanding of vector spaces and embedded vectors, and you can apply this knowledge to develop efficient and accurate AI models. You are proficient in Data Architecture and ETL: You have experience designing and implementing robust data architectures and ETL (Extract, Transform, Load) pipelines to ensure seamless data flow and integrity. You have expertise in SQL and NoSQL Databases: You are proficient in working with both SQL and NoSQL databases, and you can efficiently query and manipulate data to support AI model development and deployment. You leverage Testing and CI/CD: You are well-versed in testing methodologies and have experience implementing continuous integration and continuous deployment (CI/CD) pipelines to ensure code quality and streamline the development process. You are an expert in Code Review and Collaboration: You have a strong understanding of code review best practices and enjoy collaborating with team members to maintain high-quality code and share knowledge. You know Agile Methodologies: You are familiar with Agile development methodologies, such as Scrum or Kanban, and can effectively work in an Agile environment to deliver iterative and incremental value. You live in Cross-Team Collaboration: You thrive in a collaborative environment, working effectively with cross-functional teams, including data scientists, software engineers, and product managers, to deliver high-quality AI solutions. You are Continuous Learning and Adaptable: You stay up-to-date with the latest advancements in AI, ML, and data engineering, and you are eager to learn and adapt to new technologies and methodologies.

Requirements

You have AI and ML Expertise: You have a deep understanding of artificial intelligence and machine learning concepts, with extensive experience in developing and deploying AI models and algorithms.
You are proficient in Python: You possess strong programming skills in Python, with the ability to write clean, efficient, and scalable code.
You have Foundational Model Experience: You have hands-on experience working with foundational models such as RAG (Retrieval-Augmented Generation), and you are well-versed in their applications and limitations.
You are proficient in API Building: You have experience building and designing APIs using frameworks like Flask, ensuring seamless integration and interaction between different systems and components.
You are proficient in AWS tools: You are proficient in utilizing AWS services and tools for data storage, processing, and deployment of AI models.
You are proficient in Big Data: You have expertise in large-scale data processing and analysis, and you are comfortable working with big data technologies.
You have Vector and Embedded Vector Knowledge: You have a solid understanding of vector spaces and embedded vectors, and you can apply this knowledge to develop efficient and accurate AI models.
You are proficient in Data Architecture and ETL: You have experience designing and implementing robust data architectures and ETL (Extract, Transform, Load) pipelines to ensure seamless data flow and integrity.
You have expertise in SQL and NoSQL Databases: You are proficient in working with both SQL and NoSQL databases, and you can efficiently query and manipulate data to support AI model development and deployment.
You leverage Testing and CI/CD: You are well-versed in testing methodologies and have experience implementing continuous integration and continuous deployment (CI/CD) pipelines to ensure code quality and streamline the development process.
You are an expert in Code Review and Collaboration: You have a strong understanding of code review best practices and enjoy collaborating with team members to maintain high-quality code and share knowledge.
You know Agile Methodologies: You are familiar with Agile development methodologies, such as Scrum or Kanban, and can effectively work in an Agile environment to deliver iterative and incremental value.
You live in Cross-Team Collaboration: You thrive in a collaborative environment, working effectively with cross-functional teams, including data scientists, software engineers, and product managers, to deliver high-quality AI solutions.
You are Continuous Learning and Adaptable: You stay up-to-date with the latest advancements in AI, ML, and data engineering, and you are eager to learn and adapt to new technologies and methodologies.

Responsibilities

Develop AI Models and Algorithms: Design, implement, and optimize advanced AI models and algorithms using Python, foundational models like RAG, and other relevant technologies.
Build and Integrate APIs: Design and develop robust APIs using frameworks like Flask to facilitate seamless integration and interaction between AI models, tools, and other systems.
Integrate AI into Tools and Applications: Collaborate with cross-functional teams to integrate AI capabilities into user-friendly tools and applications, focusing on enhancing functionality and user experience.
Utilize AWS for AI Deployment: Leverage AWS services and tools to deploy, scale, and manage AI models and applications in a secure and efficient manner.
Perform Large-Scale Data Processing: Use big data technologies to process and analyze vast amounts of data, enabling the development of accurate and insightful AI models.
Design Data Architectures and ETL Pipelines: Develop robust data architectures and ETL pipelines to ensure smooth data flow, data quality, and data integrity throughout the AI development lifecycle.
Implement Testing and CI/CD: Develop and execute comprehensive testing strategies and implement CI/CD pipelines to ensure code quality, reliability, and efficient deployment of AI models and applications.
Conduct Code Reviews: Actively participate in code reviews, providing constructive feedback and ensuring adherence to coding best practices and standards.
Optimize AI Performance and Scalability: Continuously monitor and optimize the performance and scalability of AI models and applications, ensuring they meet the highest standards of efficiency and reliability.
Collaborate and Innovate: Work closely with UI/UX engineers, software engineers, and product managers to ideate, prototype, and implement innovative AI solutions that push the boundaries of what's possible.
Stay at the Forefront of AI Research: Keep abreast of the latest research and advancements in AI, ML, and data engineering, and apply this knowledge to drive innovation and improve our AI-powered tools and GenAI solutions.