Imagine if one of the world’s leading biomedical investment firms (that’s also getting into other areas like climate tech) made decades of its notes, investment theses, competitive landscape maps, and track record available to an AI development team charged with creating an AI that could help to identify innovations worth funding. It’s the ultimate application of AI, so hard that it’s not possible today but might become possible in the coming five years. Today, are breaking down every step of the investment analysis process to build the AI agents that make sense. But the goal is nothing short of creating an AI that won’t miss any innovation work funding and can even re-underwrite a portfolio and call out when investments that once made sense no longer do due to new information. And we have access to just about any public data set and many private ones that are available with subscription. But more importantly, we have the chance to build a system that will hybridize with a proven team of analysts and investors who is committed to mentoring the AIs we are developing, flagging their errors and teaching how they would get to the right answer. Anyone interested in developing great AIs knows that this last ingredient is key. If you have the right skills and ideas and truly embrace a team-approach, come join our sandboxes. Our work feels like play, and when our investments succeed, people live longer, healthier lives. Doesn’t get better than that.
Role Overview
As a software engineer within the AI/ML space, you'll be instrumental in developing and implementing AI/ML solutions that transform how we identify and evaluate investment opportunities in biomedical technologies. You'll work at the intersection of software development, large language models, predictive analytics, and investment analysis.
Key Responsibilities
Design and develop end-to-end AI applications, from concept through deployment
Create and optimize deep learning models for diverse data types (time-series, business data, images) and prediction tasks
Build and enhance large language models trained on proprietary research data
Implement real-time prediction systems operating on various timescales (millisecond to daily)
Develop full-stack AI applications with both frontend and backend components
Optimize model performance and solve complex multi-layered data challenges
Academic & Experience Requirements
Master's or Ph.D. in a Computer Science – Machine Learning field required
Extensive academic or professional background in Computer Science with AI specialization
2-3 years of professional software engineering experience
Healthcare and/or finance industry experience strongly preferred
Technical Requirements
Expert-level Python programming skills
Strong proficiency in JavaScript and Java
Deep understanding of machine learning fundamentals (regression, classification, clustering)
Extensive knowledge of neural networks and deep learning frameworks (PyTorch)
Proven expertise with AWS AI platforms (SageMaker, Bedrock)
Experience with containerization and orchestration (ECS, Kubernetes)
Strong foundation in algorithms and data structures
Additional Requirements
Excellent English communication skills for collaboration with team members and stakeholders
Strong problem-solving abilities and investigative mindset
Experience with full AI/ML development lifecycle
Ability to work in a collaborative, mentorship-driven environment
Ability to work in a hybrid environment in our local Boston office
What Makes This Role Unique
You'll be working with extensive proprietary datasets and building systems that directly impact investment decisions in breakthrough medical and climate technologies. Success in this role means creating AI systems that help fund innovations that can extend and improve human lives.
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Engineering and Information Technology
Industries
Financial Services
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