AI Engineer (Intern)

Juniper Square

1d•Remote

About The Position

Our mission is to unlock the full potential of private markets. Privately owned assets like commercial real estate, private equity, and venture capital make up half of our financial ecosystem yet remain inaccessible to most people. We are digitizing these markets, and as a result, bringing efficiency, transparency, and access to one of the most productive corners of our financial ecosystem. If you care about making the world a better place by making markets work better through technology – all while contributing as a member of a values-driven organization – we want to hear from you. Juniper Square offers employees a variety of ways to work, ranging from a fully remote experience to working full-time in one of our physical offices. We invest heavily in digital-first operations, allowing our teams to collaborate effectively across 27 U.S. states, 2 Canadian Provinces, India, Luxembourg, and England. We also have physical offices in San Francisco, New York City, Mumbai and Bangalore for employees who prefer to work in an office some or all of the time. We're looking for an AI Engineer Intern to join our team who is excited to help transform the private markets. In this role, you’ll work alongside a talented and collaborative team focused on one of our top strategic initiatives - bringing cutting-edge AI innovation to a key product feature that will drive real change in the industry. As an intern, you’ll have a hands-on role in designing, building, and testing new AI-driven product features. This isn’t a side project - it's a core company priority with executive visibility and high impact. You’ll work in close partnership with engineers, product leaders, and mentors who are invested in your growth and success. You’ll also gain valuable exposure to company leadership, access to world-class mentorship, and the opportunity to contribute meaningfully to a product that’s reshaping how the private markets operate. For the right person, this internship can be a launchpad into a full-time role post-graduation. This opportunity is perfect for someone with a strong engineering foundation who is currently pursuing a master’s degree in AI or a related field - and who’s excited to innovate, learn fast, and make a real-world impact. This is a remote role based in the U.S. or Canada. The internship program runs for 11 weeks at 40 hours per week, with a scheduled start date of Monday, June 8th. There may be an opportunity to travel to our San Francisco office the final week to participate in the annual Hackathon.

Requirements

Currently pursuing a Master’s degree in Computer Science, Data Science, Artificial Intelligence, Software Engineering, or a related quantitative field (e.g., Mathematics, Statistics, Physics)
Strong academic foundation with relevant coursework in algorithms, data structures, linear algebra, calculus, probability, and statistics
Completed or currently enrolled in courses in machine learning, deep learning, NLP, or computer vision (highly desirable)
Proficient in Python; experience with libraries such as TensorFlow, PyTorch, scikit-learn, NumPy, and Pandas is a plus
Familiarity with data manipulation, preprocessing, and feature engineering techniques
Exposure to databases (SQL/NoSQL) and data querying; experience with data visualization tools (e.g., Looker, Tableau, Power BI) is a bonus
Understanding of foundational ML algorithms (e.g., regression, decision trees, clustering) and the underlying mathematical concepts
A strong grasp of Large Language Model (LLM) mechanisms, including knowledge of sampling strategies, structured output generation, and function-calling capabilities. Hands-on experience with prompt engineering is a strong plus
Exposure to cloud platforms (e.g., AWS, GCP) and cloud-based ML services (e.g., Amazon SageMaker, Google AI Platform) is beneficial
Basic knowledge of software engineering practices, including version control (Git), Agile development, and API integration (REST, GraphQL)
Strong analytical and problem-solving skills with a high attention to detail
Eagerness to learn and apply new AI concepts in a fast-paced, evolving environment
Clear and effective communication skills, both written and verbal
Collaborative mindset with the ability to contribute meaningfully to team discussions and technical problem-solving
Self-starter with curiosity, initiative, and a proactive approach to innovation

Nice To Haves

Personal AI/ML projects (e.g., GitHub portfolio)
Participation in AI/ML competitions or hackathons
Research experience or academic publications in AI-related areas
Contributions to open-source projects

Responsibilities

Collaborate with engineers and product managers to design and prototype AI-powered features that directly impact a key product area at the core of our business
Contribute to the development, training, and evaluation of machine learning and natural language processing (NLP) models using industry-standard tools and frameworks
Work with large and complex datasets - performing data preprocessing, feature engineering, and analysis to support model development
Apply foundational machine learning and deep learning techniques to solve real-world problems in the private markets space
Assist with integrating AI models into production systems, including testing, validation, and iteration in collaboration with the engineering team
Support ongoing research and experimentation efforts, particularly around NLP and large language models (LLMs), to drive innovation in product development
Partner closely with engineering, design, and product stakeholders to evaluate the technical feasibility and ensure alignment of proposed AI features with the overall product vision and strategy.
Participate in regular team meetings, code reviews, and brainstorming sessions - bringing curiosity, ideas, and technical insight to the table
Receive mentorship from experienced AI and engineering leaders, while gaining exposure to company leadership and strategic initiatives
Contribute to documentation and knowledge sharing to help scale AI development efforts across the team
Take ownership of meaningful projects with the potential to influence long-term company strategy and product direction
Embrace a growth mindset - continuously learning new tools, methodologies, and concepts in the rapidly evolving field of AI