Machine Learning Engineer
Listed on 2026-07-03
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IT/Tech
Machine Learning/ ML Engineer, AI Engineer (Applied/Software), Data Scientist
Are you looking to make an impactful difference in your work, yourself, and your community? Why settle for just a job when you can land a career? At ICW Group, we are hiring team members who are ready to use their skills, curiosity, and drive to be part of our journey as we strive to transform the insurance carrier space. We’re proud to be in business for over 50 years, and its change agents like yourself that will help us continue to deliver our mission to create the best insurance experience possible.
Headquartered in San Diego with regional offices located throughout the United States, ICW Group has been named for ten consecutive years as a Top 50 performing P&C organization offering the stability of a large, profitable and growing company combined with a focus on all things people. It’s our team members who make us an employer of choice and the vibrant company we are today.
We strive to make both our internal and external communities better everyday!
The Machine Learning Engineer (MLE) selected for this role at ICW Group will build and deploy high-performing machine learning models across the enterprise. As an MLE on the rapidly growing Enterprise Analytics team, you will have the opportunity to shape the processes through which we build, deploy, and monitor models. This impactful role will put analytic applications into production that drive revenue growth, reduce expenses, and enhance the customer experience.
The insurance industry is full of complexity and is data-rich. You will collaborate closely with business partners across the enterprise in Underwriting, Claims, Finance, Actuarial, HR, Legal, and Technology to help us realize value from our extensive data resources.
ESSENTIAL DUTIES AND RESPONSIBILITIES- Build agentic and GenAI solutions to expand the use of AI throughout the organization.
- Collaborate with data scientists to make ML models production-ready and move them from the lab into live production environments.
- Help design and maintain engineering and model delivery standards.
- Create demos as well as full-featured applications.
- Put effective model monitoring and guardrails in place.
- Determine suitable AI techniques to solve stakeholder business problems.
- Collaborate effectively with data engineering and MLOps teams and recommend development patterns and process improvements.
- Ensure that internal and external data pipelines are constructed to support sophisticated data models and products.
- Work closely with IT Security and Data Governance to ensure that analytics practices meet data security, privacy, and quality policies.
- Contribute to the development of internal policies and ensure the Enterprise Analytics team is compliant with applicable regulations.
- Be willing to be in-office 3+ days per week at our sunny San Diego HQ.
- Have an interest in joining a company with a history of philanthropy and giving back, stability with over 50 years in business, flexibility with mindfulness of work-life balance, and a commitment to helping and investing in colleagues so they may become the best version of themselves.
This role does not have supervisory responsibilities.
EDUCATION AND EXPERIENCEBachelor’s degree from a four-year college or university required, with a major in Computer Science, Electrical Engineering, or a related field, and a minimum of 3–6 years of industry experience in MLE roles; or an MS, MEng, or PhD in a related field with a minimum of 1–2 years of industry experience working as an MLE or in a closely related role.
CERTIFICATES,LICENSES, REGISTRATIONS
None required.
KNOWLEDGE AND SKILLS- A track record of putting ML models into production and deploying models at scale.
- Extensive cloud computing experience using AWS.
- Proficiency with databases and database methodologies, especially Snowflake.
- Strong knowledge and experience with containers, software design patterns, unit testing, CI/CD, microservices, creating REST APIs, and agile methodologies.
- Knowledge of and experience with LLMs and generative AI, as well as some of the following: statistical and machine learning algorithms, NLP, forecasting, recommender systems, reinforcement learning,…
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