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Responsibilities
- You will be a Senior AI Engineer on the Product team where you will work on incorporating LLM powered systems into new data products, advance our existing products and help shape Apptopia’s long term AI strategy.
- You will spearhead efforts to incorporate LLM powered systems as we bring new finance focused products to market
- Design and implement agentic workflows that combine LLM reasoning, structured data, and external tools to accelerate new product delivery
- Experiment with multi-step reasoning systems, RAG, tool orchestration, and emerging paradigms to improve analyst workflows
- Design, develop, and implement machine learning algorithms to advance a broad set of use cases including app usage trend forecasting, consumer behavior prediction,, stock price movement estimation, user segmentation
- You will take part, and in many cases lead the thought process for improving core modeling efforts:
- Identify opportunities to extend existing modeling work into AI-native systems that integrate predictions, reasoning, and automation
- Identify opportunities to augment core datasets with LLM-derived features, classifications, and insights
- Research, identify, and test ensemble methodologies to continuously improve accuracy and coverage in our models used for core app usage estimates
- You will be a key thought leader in development of our AI platform and infrastructure: ○ Contribute to the design of internal AI platforms that enable teams to leverage LLMs at scale
- Lead rapid experimentation cycles to evaluate new LLM capabilities, architectures, and vendors
- Define frameworks for evaluating LLM quality, reliability, and cost-performance tradeoffs
- Partner with product and engineering to take ideas from 0 → production
- Help define best practices for prompting, memory, tool use, and system architecture
Required Qualifications
5+ years in data science, ML, data engineering, or applied AI
Experience building production ML systems end-to-end
- Hands-on experience with LLMs (OpenAI, Anthropic, Bedrock, etc.)
- Experience with RAG, tool use, or agentic systems
- Strong Python + experience with APIs and cloud (AWS preferred)
- Databricks tooling experience preferred
- Comfortable with ambiguity and fast experimentation cycles
- Familiarity with click stream, app usage, and/or observational panel data preferred
Job description provided by Cephalgo.
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