This is a fully remote opportunity.
About the role:
If you want to work on cutting edge technology with friendly, intelligent people in a highly collaborative environment, then Gradient AI is the right place for you. We are looking for full-stack engineers to integrate Machine Learning models and their insightful analysis into client-facing applications. The ideal candidate is a life-long learner who knows Python, with strong analytical skills and an interest in Machine Learning.
Gradient AI:
Gradient AI is a leading provider of AI solutions for the Group Health and P&C insurance industries. Our solutions improve loss ratios and profitability by predicting underwriting and claim risks with greater accuracy, as well as reducing quote turnaround times and claim expenses through intelligent automation. Gradient AI’s SaaS platform leverages a vast industry data lake comprising tens of millions of policies and claims, providing insurers with high resolution, data-driven insights. Customers include some of the most recognized insurance carriers, MGAs, MGUs, TPAs, risk pools, PEOs, and large self-insured employers across all major lines of insurance. Founded in 2018, Gradient has experienced strong growth every year, and recently raised $56 million in Series C funding from top Insurtech investors.
How will you make an impact:
- Collaborate with our product team to build new features.
- Participate in high-level design decisions and execute on them.
- Work closely with our data science and data engineering teams to build robust data pipelines and workflows.
- Interface with our project team to build integrations with clients.
- Leverage data infrastructure to deliver high impact, user-friendly, client-facing business intelligence and analytics.
Skills needed to succeed:
- 3+ years of experience building applications using Python, web frameworks (Django, Flask, etc), JavaScript frameworks (React, Angular, etc.) and SQL.
- Familiarity with AWS or other cloud environments a plus.
- Familiarity with Kubernetes, Docker, or another container technology a plus.
- Exposure working with Data Science teams and productionizing machine learning models is nice to have.
- Experience working in Insurtech or on AI/ML products is a bonus.
What we offer:
- A fun, team-oriented startup culture.
- Generous stock options - we all get to own a piece of what we’re building.
- Unlimited vacation days.
- Flexible schedule that supports working from home.
- Full benefits package including medical, dental, vision, 401k, and more.
- Ample opportunities to learn and take on new responsibilities.
We are an equal opportunity employer.
Top Skills
What the Team is Saying
What We Do
Gradient AI is a leading provider of AI solutions for the Group Health and P&C insurance industries. Our solutions improve loss ratios and profitability by predicting underwriting and claim risks with greater accuracy, as well as reducing quote turnaround times and claim expenses through intelligent automation. Gradient AI’s SaaS platform leverages a vast industry data lake comprising tens of millions of policies and claims, providing insurers with high resolution, data-driven insights. Customers include some of the most recognized insurance carriers, MGAs, MGUs, TPAs, risk pools, PEOs, and large self-insured employers across all major lines of insurance. Founded in 2018, Gradient has experienced strong growth every year, and recently raised $56 million in Series C funding from top Insurtech investors.
Why Work With Us
Here at Gradient, we emphasize learning and development for all employees while offering ample opportunities to learn and take on new responsibilities in a fast-paced, growth-mode startup. Grow your skills and your career as our company expands all while learning about AI, ML, and InsureTech, a cutting edge industry disrupting the space!
Gallery
Gradient AI Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
Working from the office is optional if you are local to our Boston office. For employees who do come in, it’s usually T/W/Th to focus on group collaboration.
