Job Description

Roles & Responsibilities

Key Responsibilities:

• 
  
• Design, build, and deploy AI/ML models and applications across several concurrent projects
• 
  
• Rapidly prototype proof-of-concepts to validate AI use cases for the business
• 
  
• Integrate large language models (LLMs) and AI APIs (OpenAI, Anthropic, etc.) into internal tools and products
• 
  
• Build and maintain data pipelines to support model training and inference
• 
  
• Collaborate with cross-functional teams (product, data, business units) to translate requirements into AI solutions
• 
  
• Optimize models for performance, cost, and scalability in production
• 
  
• Write clean, maintainable, well-documented code
• 
  
• Stay current with emerging AI tools, frameworks, and best practices
• 
  
• Prioritize and manage multiple parallel initiatives with shifting deadlines
• 
  

Preferred Qualifications:

• 
  
• Experience with vector databases, RAG (Retrieval-Augmented Generation) architectures
• 
  
• Familiarity with MLOps tools and CI/CD pipelines
• 
  
• Experience deploying models via containerization (Docker/Kubernetes)
• 
  
• Background in NLP, computer vision, or data engineering
• 
  
• Prior experience in a fast-paced startup or innovation team setting

Job Description

Roles & Responsibilities

Key Responsibilities:

• 
  
• Design, build, and deploy AI/ML models and applications across several concurrent projects
• 
  
• Rapidly prototype proof-of-concepts to validate AI use cases for the business
• 
  
• Integrate large language models (LLMs) and AI APIs (OpenAI, Anthropic, etc.) into internal tools and products
• 
  
• Build and maintain data pipelines to support model training and inference
• 
  
• Collaborate with cross-functional teams (product, data, business units) to translate requirements into AI solutions
• 
  
• Optimize models for performance, cost, and scalability in production
• 
  
• Write clean, maintainable, well-documented code
• 
  
• Stay current with emerging AI tools, frameworks, and best practices
• 
  
• Prioritize and manage multiple parallel initiatives with shifting deadlines
• 
  

Preferred Qualifications:

• 
  
• Experience with vector databases, RAG (Retrieval-Augmented Generation) architectures
• 
  
• Familiarity with MLOps tools and CI/CD pipelines
• 
  
• Experience deploying models via containerization (Docker/Kubernetes)
• 
  
• Background in NLP, computer vision, or data engineering
• 
  
• Prior experience in a fast-paced startup or innovation team setting