Software Engineer – Machine Learning
Job in
Charlotte, Mecklenburg County, North Carolina, 28245, USA
Listed on 2026-07-20
Listing for:
100 CRC Insurance Group, LLC
Full Time
position Listed on 2026-07-20
Job specializations:
-
Software Development
Machine Learning/ ML Engineer, AI Engineer (Applied/Software)
Job Description & How to Apply Below
Job Overview
We are building the foundation of the machine learning function at a market-leading insurance company. As one of the first data science hires, you will shape our ML strategy, frameworks, and operating model while developing and maintaining production-grade solutions.
Key Responsibilities- Strategic Contribution:
Partner with the Head of ML, product and data teams to define and implement company‑wide ML framework and best practices. - Hands‑On Development:
Ideate, design and build ML and AI prototypes; develop and deploy production‑grade ML models and data pipelines; build orchestration, integration frameworks and CI/CD pipelines. - Operational Excellence:
Monitor, maintain, and retrain models in production; manage data updates, versioning and integrity; implement robust monitoring and alerting systems. - Team Building:
Establish processes, tools and standards for a growing ML team; mentor future hires and foster a collaborative, innovative culture.
Deliver high‑quality working software, automate reusable tasks, engage with business stakeholders from the design phase, refine user stories, develop automated unit testing, provide warranty support and knowledge transfer to production support.
Bachelor’s Degree and 6–10 years of experience or equivalent education/training in software engineering or related fields.
- Strong proficiency in Python and ML frameworks.
- Experience with Databricks, Azure for data engineering and ML workflows.
- Familiarity with MLOps tools (MLflow, Lakehouse Monitoring, Azure Dev Ops) and CI/CD practices.
- Solid understanding of data science and engineering principles and model lifecycle management.
- 5+ years total in data analytics, infrastructure, engineering and science roles; 2+ years in applied ML engineering or data science roles.
- Proven record of deploying ML models into production; experience with monitoring, retraining and maintaining ML systems at scale.
Ability to work independently and collaboratively in a fast‑paced environment; strong communication skills to influence stakeholders and explain technical concepts.
- Knowledge of insurance industry data and business processes.
- In‑depth knowledge of information systems and application of best practices.
- Understanding of key business processes and competitive strategies related to IT.
- Project planning, management and problem‑solving skills.
- Mentorship of less experienced teammates.
Hybrid, based in the posted locations; remote options available for the right candidate.
Benefits- Medical, dental, vision, life, disability, and AD&D insurance.
- Tax‑advantaged savings accounts and a 401(k) plan with company match.
- Generous paid time off, company holidays, vacation and sick days, new‑parent leave.
- Restricted stock units and/or deferred compensation plans for eligible positions.
CRC Group supports a diverse workforce and is an Equal Opportunity Employer that does not discriminate on the basis of race, gender, color, religion, citizenship or national origin, age, sexual orientation, gender identity, disability, veteran status or other classification protected by law. CRC Group is a Drug‑Free Workplace. EEO is the law.
#J-18808-LjbffrTo View & Apply for jobs on this site that accept applications from your location or country, tap the button below to make a Search.
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).
Search for further Jobs Here:
×