AI Engineer

Zenarate uses cutting-edge speech processing, AI, and machine learning to empower contact center agents to deliver the best experience possible.

Some facts about the business: 

We are an exciting and profitable SaaS company, with 100% year-over-year growth. Profitable growth means that we have control over our destiny and you will be part of an organization that is focused on customers and employees first 

 Our platform is used in over a dozen countries and 13 languages by leading brands, including Nintendo, Google Play, Genpact, American Express, Bank Of America, and United Airlines. 

We have won multiple awards from premier organizations, including the American Business Awards (Stevies). 

 Our Management team has a very successful track record of building multiple successful companies.

You will be part of building a disruptive, $1B+ business following the demand curve of AI in the contact centers.  

About the Position 

As an AI Engineer, you will be responsible for designing, developing, and implementing artificial intelligence solutions to solve complex problems across various domains. You will work closely with cross-functional teams to understand business requirements, identify opportunities for AI integration, and develop innovative solutions that leverage machine learning, deep learning, natural language processing, computer vision, and other AI techniques. The ideal candidate will have a strong background in computer science, mathematics, and AI, along with hands-on experience in building and deploying AI models in real-world applications. 

Responsibilities: 

• Collaborate with stakeholders to understand business objectives and requirements for AI solutions. 

• Research, design, and develop AI algorithms and models to address specific business challenges. 

• Implement machine learning, deep learning, and other AI techniques to analyze large datasets and extract meaningful insights. 

• Build scalable and robust AI systems that can handle real-time data processing and analysis. 

• Optimize AI models for performance, accuracy, and scalability, considering factors such as computational resources and latency requirements. 

• Develop data pipelines and workflows to collect, preprocess, and prepare data for training and inference. 

• Evaluate and benchmark different AI algorithms and frameworks to identify the most suitable approach for specific use cases. 

• Collaborate with software engineers to integrate AI components into existing systems and applications. 
• Conduct thorough testing and validation of AI models to ensure reliability, robustness, and generalization.