Ai Engineer

Summary

Join Fantasy, a digital product and innovation company, as an AI Engineer. Your primary responsibility will be to conceptualize, develop, and deploy AI solutions for our clients. You will work with cross-functional teams, integrating AI and machine learning models into our infrastructure. The role involves a mix of research (35%) and engineering (65%), focusing on creating novel AI-enabled digital experiences. You will manage AI Ops, stay updated on industry trends, and collaborate effectively within a dispersed team. This position requires a Bachelor's degree in a relevant field and 3+ years of experience in software engineering, data science, or machine learning engineering.

Requirements

• Bachelor's degree in Computer Science, AI, Data Science, Machine Learning, Applied Mathematics or a similar field of study, or equivalent work experience
• 3+ years of experience in software engineering, data science, or machine learning engineering within an experience design or technology agency, enterprise, or a software company
• Project-proven programming abilities, with a preference for Python and AI SDKs; Node with AI feature-rich implementations will be considered
• Flexibility with contributing AI components on a multi-language application as part of a larger team or building prototype soup-to-nuts yourself
• Expert understanding of LLMs including prompt engineering, Retrieval Augmented Generation (RAG), fine-tuning, and Low-Rank Adaptation (LoRA) techniques
• Experience with models, such as LLaMA, Gemini, OpenAI GPT, and open-source models
• Exposure to foundation language (LLM) and vision, audio, and multi-modal models
• Experience with AI/LLM frameworks, like LangChain, LlamaIndex, Semantic Kernel, and OpenAI Agents SDK
• Ability to optimize AI algorithms and models for efficiency, accuracy, and scalability, leveraging best practices and emerging technologies in the field
• Experience with data exchange formats (JSON, YAML) to ensure structured outputs
• Strong knowledge of Vector databases; comfort with SQL, NoSQL and/or Graph data
• Experience with cloud computing systems: Azure, AWS, and or Google Cloud Platform
• Able to develop synchronous and asynchronous programming structures
• Strong proficiency with data and ML-adjacent Python libraries (pandas, scikit-learn, etc)
• Passion for AI: You geek out on generative AI, data science and machine learning theory and industry developments
• Exceptional verbal, written, and presentation skills
• Ability to work collaboratively in a cross-functional team environment
• Experience with version control, especially Git

Responsibilities

• Conceptualize, develop, and deploy AI solutions to power features and product enhancements
• Work as part of software engineering teams to integrate AI and machine learning models, algorithms, and data pipelines into the infrastructure
• Rapidly prove and give form to novel AI-enabled digital experiences through functional prototyping, with a focus on frequent sharable demo releases for stakeholders
• Support the design, architecture, and implementation of scalable systems that support AI-powered functionalities, ensuring high performance, reliability, security, and responsible AI
• Manage AI Ops including model server infrastructures, cloud service quotas, endpoint deployments, model/API uptime and response time
• Stay abreast of industry trends, advancements, and emerging technologies in AI, agent systems, machine learning, and backend development
• Conduct project-driven research initiatives, designing appropriate research methodology and acceptance criteria based on specific project needs
• Define and estimate your accountable tasks and maintain status (e.g., Asana, Jira)
• Test, review, and release code using version control within continuous delivery
• Document key architecture decision points, reasons, and alternatives explored
• Work effectively independently and as part of a dispersed team of experts, which can vary from single engineer prototypes to initiatives that extend across time zones and continents

Preferred Qualifications

• Proficient understanding of typical AI tooling ecosystem including knowledge and experience of containerization platforms (e.g., Kubernetes), MLOps and AIOps tools
• Foundational understanding of machine learning concepts, algorithms, and techniques
• Experience or knowledge of AI model training techniques
• Experience with graph data structures and application for AI
• Strong communication skills; can represent the Fantasy brand with clients or the broader AI community
• Experience setting up and deploying web applications and managing CI/CD integrations
• Front end experience a plus