Machine Learning Engineer
Charlotte, NCFull-timePosted 3mo agoStill listed today
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Job overview
CRC Group is building its machine learning function and seeks a hands-on engineer to develop and maintain production-grade ML solutions while helping shape strategy, frameworks, and operating practices. The role partners with product, data, and business teams to build models and pipelines, support their deployment and operation, and establish standards for a growing team. It also contributes to mentoring and complex software initiatives.
Skills & qualifications
Skills
Qualifications
Benefits
Full job description
The position is described below. If you want to apply, click the Apply button at the top or bottom of this page. You'll be required to create an account or sign in to an existing one.
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Regular or Temporary: RegularLanguage Fluency: English (Required) Work Shift: 1st Shift (United States of America)Please review the following job description: 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 play a pivotal role in shaping our ML strategy, frameworks, and operating model. This is a unique opportunity to be hands-on, developing and maintaining production-grade solutions while influencing the long-term vision and scaling of our ML capabilities.
Key Responsibilities Strategic Contribution
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Partner with the Head of ML, product and data teams to define and implement the company-wide ML framework and best practices.
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Contribute to the roadmap for ML development, adoption and team growth.
Hands-On Development
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Ideate, design and build ML and AI prototypes to validate priority use cases and solve complex business problems to drive tangible value, while collaborating with product and business teams.
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Develop and deploy production-grade ML models and data pipelines.
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Build orchestration and integration frameworks for ML models and pipelines.
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Develop and maintain CI/CD pipelines for ML solutions, including test automation, to ensure successful deployment of updated models
Operational Excellence
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Monitor, maintain, and retrain models in production to ensure performance and compliance.
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Manage data updates, versioning, and integrity for deployed solutions.
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Implement robust monitoring and alerting systems for ML services.
Team Building
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Help establish processes, tools, and standards for a growing ML team.
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Mentor future hires and contribute to a collaborative, innovative culture.
ESSENTIAL DUTIES AND RESPONSIBILITIES Following is a summary of the essential functions for this job. Other duties may be performed, both major and minor, which are not mentioned below. Specific activities may change from time to time.
- Develop customized coding, software integration, perform analysis, configure solutions, using tools specific to the project or the area.
- Lead and participate in the development, testing, implementation, maintenance, and support of highly complex solutions in adherence to company standards, including robust unit testing and support for subsequent release testing.
- Build non-functional monitoring capabilities and provide escalated support for highly complex applications in production.
- Build in and maintain security controls and monitoring in support of company standards.
- Typically lead moderately complex projects and participate in larger, more complex initiatives.
- Solve complex technical and operational problems. Act as a resource for teammates with less experience
- May oversee the work of a small team.
- In an Agile environment: Responsible for delivering high quality working software and automating manual/reusable tasks working directly, and engage with, the business from the beginning of the design work. Leverage continuous engineering practices to deliver business value regarding effectiveness of the design. Actively participate in refining user stories. Responsible for design, developing, and maintaining automated unit testing, and supporting integration and functional testing. Responsible for providing automated monitoring capabilities, providing warranty support, and providing knowledge transfer to production support. Develop code in accordance with the acceptance criteria established by the Product Owner.
QUALIFICATIONS Required Qualifications: The requirements listed below are representative of the knowledge, skill and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
- Bachelor’s Degree and six to ten years of experience or equivalent education and software engineering training or experience Technical Skills
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Strong proficiency in Python and ML frameworks.
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Experience with Databricks and Azure for data engineering and ML workflows.
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Familiarity with MLOps tools (MLflow, Lakehouse Monitoring, Azure DevOps) and CI/CD practices.
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Solid understanding of data science and engineering principles and model lifecycle management.
Experience
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5+ years total in data analytics, infrastructure, engineering and science roles.
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2+ years in applied ML engineering or data science roles.
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Proven track record of deploying ML models into production environments.
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Familiarity with monitoring, retraining, and maintaining ML systems at scale.
Soft Skills
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Ability to work independently and collaboratively in a fast-paced environment.
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Strong communication skills to influence stakeholders and explain technical concepts.
Nice-to-Have:
- Knowledge of insurance industry data and business processes
- In-depth knowledge in information systems and ability to identify, apply, and implement best practices
- Understanding of key business processes and competitive strategies related to the IT function
- Ability to plan and manage projects and solve complex problems by applying best practices
- Ability to provide direction and mentor less experienced teammates. Ability to interpret and convey complex, difficult, or sensitive information
Location: Charlotte, Dallas, Raleigh, Alpharetta
General Description of Available Benefits for Eligible Employees of CRC Group: At CRC Group, we're committed to supporting every aspect of teammates' well-being – physical, emotional, financial, social, and professional. Our best-in-class benefits program is designed to care for the whole you, offering a wide range of coverage and support. Eligible full-time teammates enjoy access to medical, dental, vision, life, disability, and AD&D insurance; tax-advantaged savings accounts; and a 401(k) plan with company match. CRC Group also offers generous paid time off programs, including company holidays, vacation and sick days, new parent leave, and more. Eligible positions may also qualify for restricted stock units and/or a deferred compensation plan.
CRC Group supports a diverse workforce and is an Equal Opportunity Employer that does not discriminate against individuals 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 Pay Transparency Nondiscrimination Provision E-Verify
How this job compares
Set against the 6,070 open Machine Learning Engineer jobs on Olive Jobs, counted November 10, 2026.
- Pay
- This postingNot listed
- North Carolina median$124–230K/yr87 salary ranges
- US median$34–68/hr109 hourly ranges
- Openings
- Olive Jobs lists 105 open Machine Learning Engineer jobs in North Carolina and 6,070 across the US. 7% of them nationwide are listed as remote or flexible.
- Experience
- This posting asks for at least 5 years of experience; Machine Learning Engineer postings that state a minimum ask for 5 years at the median (4,885 postings).
- Education
- 1,990 of the 6,070 open Machine Learning Engineer jobs (33%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 10, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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