
AI Engineer
7 hours ago
As a senior data scientist, you will have the opportunity to work at the intersection of software development, machine learning, and financial data, delivering real-world impact from day one.
You will design and build robust, maintainable software systems to support data pipelines, analytics, and AI applications. You'll collaborate with domain experts to scope, build, and iterate on AI-driven tools tailored to business needs.
To excel in this role, you should have strong programming skills in Python and proficiency with SQL and relational databases. Experience working with data pipelines, ETL workflows, and data wrangling techniques is also essential. Additionally, you should have familiarity with ML frameworks and data libraries, exposure to generative AI or LLM APIs and frameworks, and an understanding of fundamental machine learning and data science concepts.
We're looking for a team player who can create clean, intuitive user interfaces and data visualizations. Optimizing database access and performance for large structured and semi-structured datasets is also crucial. Our ideal candidate is someone who ensures tools are scalable, secure, and aligned with end-user workflows and UX needs.
">Key Responsibilities:">- ">
- Design and build robust, maintainable software systems to support data pipelines, analytics, and AI applications.">
- Collaborate with domain experts to scope, build, and iterate on AI-driven tools tailored to business needs.">
- Develop efficient data ingestion, transformation, and validation pipelines using Python, SQL, and modern libraries.">
- Integrate large language models (LLMs) and generative AI APIs into internal tooling.">
- Create clean, intuitive user interfaces and data visualizations.">
- Optimize database access and performance for large structured and semi-structured datasets.">
- Ensure tools are scalable, secure, and aligned with end-user workflows and UX needs.">
- ">
- Strong programming skills in Python.">
- Proficiency with SQL and relational databases.">
- Experience working with data pipelines, ETL workflows, and data wrangling techniques.">
- Familiarity with ML frameworks and data libraries.">
- Exposure to generative AI or LLM APIs and frameworks.">
- Understanding of fundamental machine learning and data science concepts.">
- Strong written and verbal communication skills.">
- User-focused mindset: you care about who's using your tools and how to make them intuitive.">
- Team-oriented: you work well with others.">
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