Posted on May 12

β€’ 3 days to apply

AI/ML Engineer - Applied AI Systems Builder

$97 - $130 per hour

Job InformationDuration: >6 months β€’ 20-30 hrs/weekStatus: US-based applicants onlyType: Remote / In-Person Position
Description
Seeking an experienced AI/ML Engineer to design and build bespoke AI systems that support deal sourcing, underwriting, and operational improvement across the firm. This is a technical builder role focused on creating internal AI tools tailored to the specific needs of investment professionals. You'll work with sophisticated team members to understand their requirements, build or integrate AI solutions (including custom LLM applications, data pipelines, and analytical tools), and iterate based on feedback. Background should include hands-on experience building production AI systems, ideally in financial services or private equity environments. Role requires someone who can work independently, communicate clearly with non-technical stakeholders, and deliver working solutions quickly. This is a fractional engagement with potential to scale to multiple concurrent projects as the firm expands its AI capabilities.
Skills
Machine Learning
AI
Python
Claude
Databricks
Large Language Models
Data Engineering
API Integration
Data pipelines
Financial services
Private equity
Agile
Responsibilities
  • Design and build custom AI systems for specific investment workflows (deal identification, underwriting, operational analysis)
  • Work with investment professionals to understand requirements and translate them into technical solutions
  • Integrate third-party AI tools and platforms (e.g., Claude, Databricks) with internal systems
  • Build data pipelines and ETL processes to support AI applications
  • Answer technical questions and mentor investment professionals on AI capabilities and limitations
  • Iterate on prototypes based on user feedback
  • Maintain code quality and documentation for long-term maintainability
  • Support A/B testing and evaluation of different AI approaches
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$97 - $130 per hour

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Screening Questions (Required)
Question 1: Describe a production AI system you've built from scratch. What was the use case, what tools and frameworks did you use, and how did you measure success?
Question 2: Have you worked in financial services or PE before? If so, how did you tailor AI solutions to the constraints and workflows of that industry?
Question 3: How do you approach building AI systems that need to be understood and used by non-technical domain experts? Can you give an example of how you communicated model limitations or explained why something didn't work?
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