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

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)

Benefits

Health insurance
Remote work options
Professional development opportunities

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

machine learningdeep learningnatural language processingdata preprocessingfeature engineeringPythonalgorithmsdata structureslinear algebrastatistics

Soft Skills

collaborationcuriosityinnovationownershipgrowth mindsetcommunicationmentorshiptechnical insightproblem-solvingteamwork

Certifications

Master’s degree in Computer ScienceMaster’s degree in Data ScienceMaster’s degree in Artificial IntelligenceMaster’s degree in Software Engineering