Machine Learning Engineer
About CorgiCorgi is a full-stack insurance carrier building better, faster insurance products for startups. We’re not a broker, so we underwrite and issue policies directly, with fewer handoffs and less friction. Cutting out intermediaries lets us tailor coverage to how companies actually operate and price risk more efficiently. We build insurance products from the ground up, using AI and software to automate the workflows traditionally handled by large teams of brokers, underwriters, TPAs, accountants, and operations staff. Our goal is not to incrementally improve insurance, it is to rebuild the industry infrastructure itself. We move quickly, care deeply about talent density, and hire people who want to solve difficult problems with unusually high ownership.
About the Role:
We're hiring a Machine Learning Engineer to develop and deploy machine learning systems that power our insurance companies and internal operations. You will work closely with engineering, product, operations, and leadership to build models and intelligent systems across underwriting, risk assessment, claims, finance, and internal operations. This is a highly hands-on role for someone who enjoys solving complex technical problems, experimenting with new approaches, and turning machine learning research into reliable production systems.
What You'll Do:
Build predictive models for risk assessment, underwriting, pricing, fraud detection, and claims analysis.
Develop and maintain scalable ML pipelines for data processing, feature engineering, model training, and inference.
Experiment with deep learning, foundation models, and modern machine learning architectures.
Work with large, complex datasets to identify patterns, improve predictions, and automate decision-making workflows.
Collaborate with underwriters, actuaries, and domain experts to translate complex business problems into machine learning solutions.
Contribute to ML infrastructure, experimentation frameworks, and engineering standards as the team grows.
Who You Are:
Strong software engineering fundamentals with a deep understanding of machine learning principles.
Comfortable taking machine learning projects from experimentation through production deployment.
Strong analytical and problem-solving skills with an ability to work with complex datasets.
Curious about emerging machine learning research and motivated to apply new techniques to real-world problems.
Comfortable working in ambiguity, moving quickly, and iterating based on results.
High ownership and bias toward execution.
Excited to work closely with engineers, operators, and domain experts.
Interested in building machine learning systems that directly impact how businesses operate.
Preferred Experience 3+ years of experience in machine learning, software engineering, or a related technical field.
Strong proficiency in Python and experience with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn.
Experience developing, training, evaluating, and deploying machine learning models.
Strong understanding of supervised learning, deep learning, statistical modeling, and model evaluation.
Experience with data processing, feature engineering, and large-scale datasets using SQL, Pandas, or similar tools.
Familiarity with ML infrastructure, model serving, training pipelines, and MLOps practices.
Experience with cloud infrastructure and services such as AWS.Familiarity with LLMs, transformers, fine-tuning, or other modern AI architectures.
Built and experimented with personal machine learning projects, research, or open-source tools.
Experience in fintech, insurance, risk modeling, or workflow automation is helpful but not required.
Why Join:
Build foundational machine learning systems for a new kind of insurance company.
Work directly with senior leadership and core operators.
Apply advanced machine learning techniques to complex, real-world problems.
High ownership and visibility from day one.
Competitive compensation and equity.
Opportunity to help define how insurance infrastructure is built in the AI era.
Office corgi (we have a couple!)