AI/Machine Learning Software Engineer

OVERVIEW: 

This role is for a mid-level AI/ML Software Engineer working with our Percipio - Search & Recommendations, Engagement and AI team.  This team supports our Conversation AI Simulator (CAISY).  This is an innovative generative AI based tool for simulating business and leadership conversational skills. CAISY makes those difficult work conversations easier, by providing employees with an emotionally safe space to practice important business conversations with an AI-powered trainer. CAISY not only plays the role of the other person within the conversation but also provides personalized feedback and guidance on communication style to guide development.

OPPORTUNITY HIGHLIGHTS & RESPONSBILITIES: 

• Hands-on AI/ML software engineer that will apply AI to solutions in the learning space
• Prompt engineering and associated reliab
• Work with product owners and curators to understand requirements and guide new features
• Collaborate with team to design, develop, and maintain application systems utilizing AI
• Document designs and implementation to ensure consistency and alignment with standards
• Create documentation including system, APIs, data structures, and sequence diagrams
• Create appropriate data pipelines for AI/ML
• Analyze, curate, cleanse, and split data
• Utilize and apply generative AI within new products/features and for daily productivity
• Periodically explore new technologies and design patterns with proof-of-concept
• Participate in developing best practices and improving operational processes
• Present research and work to socialize and share knowledge across the organization 

ENVIRONMENT, TOOLS & TECHNOLOGIES:

• Agile/Scrum
• Operating Systems – Mac, Linux
• JavaScript, Node.js, Python
• LLMs (OpenAI, Anthropic, open-source models)
• Vector indexing/database (RAG)
• Agentic Frameworks (LangChain, AutoGen, etc.)
• APIs GraphQL, REST
• Docker, Kubernetes
• Amazon Web Services (AWS), MS Azure OpenAI
• SQL (Postgres RDS/Aurora), NoSQL (Cassandra, Elasticsearch)
• Messaging – Kafka, RabbitMQ, SQS
• Monitoring – Prometheus, ELK
• GitHub, IDE (your choice) 

SKILLS & QUALIFICATIONS:

• Experience with generative AI and fine-tuning models (minimum of 5 years' experience and applicable degree). 
• Ability to design and document APIs, data models, service interactions
• Prompt engineering
• Familiarity with and ability to explain:
  • Testing strategies – unit, integration, system 
  • System and API security techniques 
  • Data privacy concerns 
  • Microservices architecture 
  • Vertical vs horizontal scaling 
  • Generative AI, NLP, DNN, LLMs, auto-encoders, etc.
  • Chain-of-thought and reflection

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