Job Description
Are you passionate about the intersection of AI and marketing? Here’s your chance to make a mark! We’re looking for an AI ML Research Intern to join the Office of the CTO, where you’ll help create cutting-edge AI agents that analyze enterprise marketing data and deliver actionable insights for performance marketing teams.
With access to advanced tools and frameworks, you’ll play a vital role in building a transformative product that redefines marketing intelligence.
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Skills
- Analytical mindset with a passion for problem-solving.
- Strong communication and team collaboration abilities.
- Eagerness to learn and embrace emerging technologies.
Role and Responsibilities
- Prior Research Internship experience in AI ML.
- Design and Build AI Agents: Develop intelligent agents using frameworks like LangGraph, LlamaIndex, and Semantic Kernel to unlock insights from vast marketing datasets.
- Optimize Performance: Use observability tools such as LangSmith and Langfuse to monitor, debug, and fine-tune AI agent performance.
- Integrate Memory Systems: Implement memory solutions with tools like MemGPT, LangMem, or zep, ensuring agents can retain and reference context effectively.
- Create Data Pipelines: Build scalable data pipelines and organize semantic data with vector databases like Pinecone, Chroma, or Weaviate.
- Deploy Advanced Models: Leverage platforms such as Anthropic, OpenAI, or Fireworks AI to integrate state-of-the-art natural language processing capabilities.
- Expand Agent Functionality: Incorporate toolkits like Composio and Browserbase to enhance usability and efficiency.
- Host and Deploy Agents: Use scalable solutions like LangGraph Agents API or Amazon Bedrock Agents for seamless deployment.
- Drive Innovation: Explore the latest in generative AI and propose creative solutions for improving marketing workflows.
Requirement
- Currently pursuing or recently completed a degree in computer science, data science or a related field.
- Mandate prior research Internship experience in AI ML.
- Proficiency in Python and experience with AI/ML frameworks such as PyTorch or TensorFlow.
- Hands-on experience with AI agent frameworks like LangGraph, AutoGen, or Semantic Kernel.
- Familiarity with vector databases (Pinecone, Chroma, Weaviate) and observability tools (LangSmith, Langfuse).
- Basic knowledge of APIs for ad platforms like Meta, Google Ads, or LinkedIn Ads.
- Exposure to cloud platforms (AWS, GCP, Azure) for deploying AI solutions.
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