Goosehead Insurance
Join to apply for the Machine Learning Engineer role at Goosehead Insurance.
At Goosehead Insurance, we’re changing the way people think about insurance through a technology-driven, client-first approach. By combining a powerful digital platform with an expert agent network, we empower clients to find the best coverage for their needs with transparency, efficiency, and trust at the core.
We’re building a data-driven culture that puts analytics at the center of our decision-making. Our team works on high-impact projects across underwriting, marketing, client experience, and agent performance. If you're excited to design, build, and scale production‑grade machine learning systems that power smarter decisions and automated experiences, we’d love to hear from you.
Who You Are You are an experienced Machine Learning Engineer who bridges the gap between data science and software engineering. You are passionate about building reliable, scalable, and maintainable ML systems that deliver measurable business impact. You thrive in environments where experimentation, deployment, and continuous improvement are key, and you enjoy partnering with data scientists, engineers, and product teams to bring advanced analytics into production.
Key Responsibilities
Design, build, and maintain end-to-end machine learning pipelines from data ingestion to model deployment and monitoring.
Partner with data scientists to productionize models and ensure they are performant, maintainable, and observable.
Develop robust APIs, batch processes, and streaming solutions to integrate models into business applications and workflows.
Implement MLOps practices for automated training, testing, deployment, and monitoring of models in production.
Optimize model performance and scalability, ensuring efficient use of compute and storage resources.
Collaborate with data engineering to ensure model pipelines are supported by reliable, high-quality data sources.
Stay current with advancements in ML infrastructure, frameworks, and tooling to continuously improve delivery speed and quality.
Security and Privacy Responsibilities
Follow company policies and procedures related to data security and privacy.
Participate in ongoing training for responsible AI and data handling best practices.
Treat client and company data with the highest standards of confidentiality.
Report any security, bias, or privacy incidents promptly.
Required Qualifications
5+ years of experience in machine learning engineering, data science, or software engineering.
Proficiency in Python and experience with ML frameworks such as PyTorch, TensorFlow, or Scikit-learn.
Experience building and deploying models in cloud environments (e.g., Azure, AWS, or GCP).
Strong understanding of data pipelines, feature engineering, and model lifecycle management.
Familiarity with containerization and orchestration (e.g., Docker, Kubernetes).
Solid software engineering fundamentals including version control, testing, and CI/CD.
Excellent communication and collaboration skills.
Preferred Qualifications
Experience with MLOps frameworks and tools (e.g., MLflow, Databricks, SageMaker, Vertex AI).
Familiarity with feature stores and model monitoring solutions.
Experience with distributed data processing frameworks (e.g., Spark, PySpark).
Background in insurance, financial services, or other data‑rich, regulated industries.
Exposure to experimentation and model governance frameworks.
Benefits Summary
High quality voluntary health, vision, disability, life, and dental insurance programs
401K Matching Plan
Employee Stock Purchase Plan
Paid holidays, vacation, and sick leave
Corporate sponsored programs to enhance employee physical, financial, mental, and emotional wellness
Goosehead is an equal‑opportunity employer and complies with all applicable federal, state, and local laws, rules, guidelines, and regulations. Goosehead strictly prohibits and does not tolerate unlawful discrimination against employees, applicants, or any other covered person because of race, color, religion, creed, national origin, ancestry, ethnicity, sex (including pregnancy, childbirth, and related medical conditions), sexual orientation, gender, gender identity, transgender status, age, physical or mental disability, veteran status, uniformed service, genetic information, or any other characteristic protected by applicable law. All applicants for employment and all Goosehead employees are given equal consideration based solely on job‑related factors, such as qualifications, experience, performance, and availability.
#J-18808-Ljbffr
At Goosehead Insurance, we’re changing the way people think about insurance through a technology-driven, client-first approach. By combining a powerful digital platform with an expert agent network, we empower clients to find the best coverage for their needs with transparency, efficiency, and trust at the core.
We’re building a data-driven culture that puts analytics at the center of our decision-making. Our team works on high-impact projects across underwriting, marketing, client experience, and agent performance. If you're excited to design, build, and scale production‑grade machine learning systems that power smarter decisions and automated experiences, we’d love to hear from you.
Who You Are You are an experienced Machine Learning Engineer who bridges the gap between data science and software engineering. You are passionate about building reliable, scalable, and maintainable ML systems that deliver measurable business impact. You thrive in environments where experimentation, deployment, and continuous improvement are key, and you enjoy partnering with data scientists, engineers, and product teams to bring advanced analytics into production.
Key Responsibilities
Design, build, and maintain end-to-end machine learning pipelines from data ingestion to model deployment and monitoring.
Partner with data scientists to productionize models and ensure they are performant, maintainable, and observable.
Develop robust APIs, batch processes, and streaming solutions to integrate models into business applications and workflows.
Implement MLOps practices for automated training, testing, deployment, and monitoring of models in production.
Optimize model performance and scalability, ensuring efficient use of compute and storage resources.
Collaborate with data engineering to ensure model pipelines are supported by reliable, high-quality data sources.
Stay current with advancements in ML infrastructure, frameworks, and tooling to continuously improve delivery speed and quality.
Security and Privacy Responsibilities
Follow company policies and procedures related to data security and privacy.
Participate in ongoing training for responsible AI and data handling best practices.
Treat client and company data with the highest standards of confidentiality.
Report any security, bias, or privacy incidents promptly.
Required Qualifications
5+ years of experience in machine learning engineering, data science, or software engineering.
Proficiency in Python and experience with ML frameworks such as PyTorch, TensorFlow, or Scikit-learn.
Experience building and deploying models in cloud environments (e.g., Azure, AWS, or GCP).
Strong understanding of data pipelines, feature engineering, and model lifecycle management.
Familiarity with containerization and orchestration (e.g., Docker, Kubernetes).
Solid software engineering fundamentals including version control, testing, and CI/CD.
Excellent communication and collaboration skills.
Preferred Qualifications
Experience with MLOps frameworks and tools (e.g., MLflow, Databricks, SageMaker, Vertex AI).
Familiarity with feature stores and model monitoring solutions.
Experience with distributed data processing frameworks (e.g., Spark, PySpark).
Background in insurance, financial services, or other data‑rich, regulated industries.
Exposure to experimentation and model governance frameworks.
Benefits Summary
High quality voluntary health, vision, disability, life, and dental insurance programs
401K Matching Plan
Employee Stock Purchase Plan
Paid holidays, vacation, and sick leave
Corporate sponsored programs to enhance employee physical, financial, mental, and emotional wellness
Goosehead is an equal‑opportunity employer and complies with all applicable federal, state, and local laws, rules, guidelines, and regulations. Goosehead strictly prohibits and does not tolerate unlawful discrimination against employees, applicants, or any other covered person because of race, color, religion, creed, national origin, ancestry, ethnicity, sex (including pregnancy, childbirth, and related medical conditions), sexual orientation, gender, gender identity, transgender status, age, physical or mental disability, veteran status, uniformed service, genetic information, or any other characteristic protected by applicable law. All applicants for employment and all Goosehead employees are given equal consideration based solely on job‑related factors, such as qualifications, experience, performance, and availability.
#J-18808-Ljbffr