GradientAI
Overview
Employer Industry: Insurance Technology Why consider this opportunity Generous stock options allowing employees to own a piece of the company Unlimited vacation days for work-life balance Flexible schedule supporting remote work Comprehensive benefits package including medical, dental, vision, and 401k Opportunities for professional development and taking on new responsibilities Fun, team-oriented startup culture recognized as a top place to work
Responsibilities
Develop and enhance AI/ML claims and underwriting platforms Contribute to the development and deployment of high-volume predictive models, including API development Utilize a tech stack that includes Python, Kubernetes, Git, and more in a Linux environment Participate in high-level design and architecture decisions alongside hands-on development Collaborate with data science and engineering teams to create robust ML Ops pipelines
Qualifications
Minimum of 5 years of professional software engineering experience Proficiency in Python and libraries such as Pandas, NumPy, and PyTorch Familiarity with SQL, Bash scripting, and Git Understanding of containerization tools like Docker and Kubernetes Experience working with data science teams and productionizing machine learning models is a plus
Preferred Qualifications
Exposure to AWS tools or similar cloud technologies Prior experience in a startup environment
#InsuranceTech #RemoteWork #AI #SoftwareEngineering #CareerGrowth #J-18808-Ljbffr
Employer Industry: Insurance Technology Why consider this opportunity Generous stock options allowing employees to own a piece of the company Unlimited vacation days for work-life balance Flexible schedule supporting remote work Comprehensive benefits package including medical, dental, vision, and 401k Opportunities for professional development and taking on new responsibilities Fun, team-oriented startup culture recognized as a top place to work
Responsibilities
Develop and enhance AI/ML claims and underwriting platforms Contribute to the development and deployment of high-volume predictive models, including API development Utilize a tech stack that includes Python, Kubernetes, Git, and more in a Linux environment Participate in high-level design and architecture decisions alongside hands-on development Collaborate with data science and engineering teams to create robust ML Ops pipelines
Qualifications
Minimum of 5 years of professional software engineering experience Proficiency in Python and libraries such as Pandas, NumPy, and PyTorch Familiarity with SQL, Bash scripting, and Git Understanding of containerization tools like Docker and Kubernetes Experience working with data science teams and productionizing machine learning models is a plus
Preferred Qualifications
Exposure to AWS tools or similar cloud technologies Prior experience in a startup environment
#InsuranceTech #RemoteWork #AI #SoftwareEngineering #CareerGrowth #J-18808-Ljbffr