Job description
Work Arrangement: Fully remote, overlapping US time zone working hours.
Job Type: Internship (Part-time)
Salary Range: Up to $700 per month, dependent on skills and experience
Work Schedule: 20 hours per week, with core hours between 9 AM – 1 PM EST
Locations: Remote, open to candidates from the Philippines and LatAm
About Pearl Talent:
Pearl works with the top 1% of candidates from around the world and connects them with the best startups in the US and EU. Our clients have raised over $5B in aggregate and are backed by companies like OpenAI, a16z, and Founders Fund. They’re looking for the sharpest, hungriest candidates who they can consistently promote and work with over many years. Candidates we’ve hired have been flown out to the US and EU to work with their clients, and even promoted to roles that match folks onshore in the US.
Hear why we exist, what we believe in, and who we’re building for: Watch here
Why Work with Us?
We’re not just another recruiting firm—we focus on placing candidates with exceptional US and EU founders who prioritize the long-term success of their team members. We also provide retention bonuses at 3, 6, 9, and 12 months, as well as community-driven benefits like an annual retreat.
About the Company:
Our client is building intelligent workflows for contracts and business documents. They are currently focused on turning static PDFs into structured, queryable data that powers smarter automations.
About the Role:
We are seeking an AI Engineering Intern to support AI-first initiatives. You’ll help build production-ready systems that extract, structure, and analyze data from PDF documents. You’ll work across backend, AI, and frontend systems—ideal for someone who wants hands-on experience deploying AI in real products. This is a remote position with part-time hours, ideal for someone passionate about AI and the legal tech industry.
Key Responsibilities:
1. Core AI Development (70%)
- Develop AI pipelines to extract structured data from PDFs using ML models.
- Integrate pre-trained/custom models for field detection, layout analysis, and document parsing.
- Implement OCR and computer vision techniques for layout detection and field recognition.
- Create and maintain RESTful APIs for AI services using .NET and AWS Lambda.
2. Frontend Integration (20%)
- Build and integrate React-based UIs that visualize AI outputs.
- Enhance PDF viewing with field highlighting, annotations, and feedback indicators.
- Implement user interactions and real-time processing updates.
3. Infrastructure & DevOps (10%)
- Work with AWS services like Bedrock, Textract, Lambda, and S3.
- Optimize inference pipelines and API responsiveness.
- Implement testing and monitoring strategies for AI components.
Ideal Candidate Profile:
1. Academic Background
- Pursuing a degree in CS, AI/ML, or Data Science
- Relevant coursework or projects in ML, CV, or NLP
2. Traits
- Independent, curious, and driven to solve hard problems
- Eager to learn and comfortable in fast-paced startup environments
- Detail-oriented and committed to shipping high-quality code
What You’ll Learn:
- How to ship AI/ML pipelines in production
- How to build intelligent products that power real business use cases
- Best practices in modern SaaS development
- End-to-end development: AI → backend → frontend
Must-Have:
- Proficiency in Python (for ML/AI) and JavaScript/TypeScript
- Experience with ML frameworks (TensorFlow or PyTorch)
- Familiarity with AWS services (Textract, Bedrock, Lambda, S3)
- Experience with React and RESTful APIs
- Strong problem-solving and debugging skills
- Git proficiency and collaborative workflows
Nice-to-Have:
- Experience with document processing libraries (e.g. pdfplumber, pdf-lib)
- OCR and CV tools (Tesseract, OpenCV, LayoutLM)
- NLP/text extraction experience
- Familiarity with SQL/NoSQL databases and .NET (C#)
- Docker and testing tools for ML systems
Competitive Compensation: Up to $700/month
Remote Work: Work from anywhere with flexible hours
Mentorship: Direct access to industry experts and founders
Growth Opportunities: Real ownership over AI features in production
Learning & Development: Build full-stack skills across AI, backend, and frontend
Path to Full-Time: High performers may receive full-time offers
