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Temporary Meta Machine Learning Jobs in Durham, NC

... Machine Learning Operations (MLOps) pathway. This pathway will bridge ongoing work in computer ... Health Insurance for Temporary Employees * Enhance your career with LEAD courses * Attend non ...

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Temporary Meta Machine Learning information

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How much do temporary meta machine learning jobs pay per hour?

As of Jul 29, 2026, the average hourly pay for temporary meta machine learning in Durham, NC is $22.05, according to ZipRecruiter salary data. Most workers in this role earn between $19.04 and $24.62 per hour, depending on experience, location, and employer.

What are some common challenges faced by professionals in temporary machine learning roles at Meta, and how can they be addressed?

Professionals in temporary machine learning roles at Meta often encounter challenges such as quickly acclimating to complex codebases, integrating with established teams, and delivering impactful results within a limited timeframe. Success in these roles typically requires strong technical skills, adaptability, and effective communication. Proactively seeking guidance, leveraging available documentation, and collaborating closely with permanent team members can help overcome these hurdles and maximize contributions during the temporary assignment.

What is the difference between Temporary Meta Machine Learning vs Data Scientist?

AspectTemporary Meta Machine LearningData Scientist
CredentialsTypically requires a background in computer science, statistics, or related fields; certifications in machine learning or data analysis are commonRequires a degree in computer science, statistics, or related fields; certifications like Certified Data Scientist are advantageous
Work EnvironmentProject-based, often contract roles within tech companies, startups, or consulting firmsFull-time or contract roles in various industries including finance, healthcare, and tech
Industry UsagePrimarily in tech, AI, and machine learning-focused companiesWidely used across multiple industries including finance, healthcare, marketing, and tech

Temporary Meta Machine Learning roles focus on short-term projects involving machine learning model development and deployment, often requiring specialized technical skills. Data Scientist roles are broader, encompassing data analysis, statistical modeling, and insights generation across diverse industries. While both roles require strong analytical skills and technical knowledge, Temporary Meta Machine Learning positions are more specialized in AI and machine learning applications.

What are the key skills and qualifications needed to thrive as a Temporary Meta Machine Learning Engineer, and why are they important?

To thrive as a Temporary Meta Machine Learning Engineer, you need a strong background in computer science, statistics, and machine learning, typically with experience in Python and relevant ML frameworks. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms, and version control systems is often required, along with a proven ability to rapidly learn new technologies. Strong problem-solving skills, adaptability, and effective communication are essential for collaborating within dynamic teams and meeting project goals on tight timelines. These skills ensure that you can quickly contribute to impactful ML projects, deliver results efficiently, and integrate well into fast-paced, innovative environments.

What are Temporary Meta Machine Learning jobs?

Temporary Meta Machine Learning jobs are short-term positions at Meta (formerly Facebook) that focus on developing, deploying, or researching machine learning models and technologies. These roles may support ongoing projects, fill gaps during employee leave, or address spikes in workload. Responsibilities can include data preprocessing, model training, evaluation, and collaborating with cross-functional teams. Temporary roles often give candidates exposure to Meta's cutting-edge AI tools and processes, and may sometimes lead to permanent opportunities.
What are the most commonly searched types of Meta Machine Learning jobs in Durham, NC? The most popular types of Meta Machine Learning jobs in Durham, NC are:
What are popular job titles related to Temporary Meta Machine Learning jobs in Durham, NC? For Temporary Meta Machine Learning jobs in Durham, NC, the most frequently searched job titles are:
What job categories do people searching Temporary Meta Machine Learning jobs in Durham, NC look for? The top searched job categories for Temporary Meta Machine Learning jobs in Durham, NC are:
What cities near Durham, NC are hiring for Temporary Meta Machine Learning jobs? Cities near Durham, NC with the most Temporary Meta Machine Learning job openings:
Infographic showing various Temporary Meta Machine Learning job openings in Durham, NC as of July 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, 1% Temporary, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $45,869 per year, or $22.1 per hour.

Machine Learning Engineer

Tihinsurance

Morrisville, NC

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 2 days ago

New


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.

If you have a disability and need assistance with the application, you can request a reasonable accommodation. Send an email to Accessibility (accommodation requests only; other inquiries won't receive a response).

Regular or Temporary:

Regular

Language 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

  • Partner with the Head of ML, product and data teams to define and implement the company-wide ML framework and best practices.

  • Contribute to the roadmap for ML development, adoption and team growth.

Hands-On Development

  • 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.

  • Develop and deploy production-grade ML models and data pipelines.

  • Build orchestration and integration frameworks for ML models and pipelines.

  • Develop and maintain CI/CD pipelines for ML solutions, including test automation, to ensure successful deployment of updated models

Operational Excellence

  • Monitor, maintain, and retrain models in production to ensure performance and compliance.

  • Manage data updates, versioning, and integrity for deployed solutions.

  • Implement robust monitoring and alerting systems for ML services.

Team Building

  • Help establish processes, tools, and standards for a growing ML team.

  • 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.
1. Develop customized coding, software integration, perform analysis, configure solutions, using tools specific to the project or the area.
2. 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.
3. Build non-functional monitoring capabilities and provide escalated support for highly complex applications in production.
4. Build in and maintain security controls and monitoring in support of company standards.
5. Typically lead moderately complex projects and participate in larger, more complex initiatives.
6. Solve complex technical and operational problems. Act as a resource for teammates with less experience
7. May oversee the work of a small team.
8. 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.
1. Bachelor's Degree and six to ten years of experience or equivalent education and software engineering training or experience

Technical Skills

  • Strong proficiency in Python and ML frameworks.

  • Experience with Databricks and Azure for data engineering and ML workflows.

  • Familiarity with MLOps tools (MLflow, Lakehouse Monitoring, Azure DevOps) and CI/CD practices.

  • Solid understanding of data science and engineering principles and model lifecycle management.

Experience

  • 5+ years total in data analytics, infrastructure, engineering and science roles.

  • 2+ years in applied ML engineering or data science roles.

  • Proven track record of deploying ML models into production environments.

  • Familiarity with monitoring, retraining, and maintaining ML systems at scale.

Soft Skills

  • Ability to work independently and collaboratively in a fast-paced environment.

  • Strong communication skills to influence stakeholders and explain technical concepts.

Nice-to-Have:

  • Knowledge of insurance industry data and business processes


2. In-depth knowledge in information systems and ability to identify, apply, and implement best practices
3. Understanding of key business processes and competitive strategies related to the IT function
4. Ability to plan and manage projects and solve complex problems by applying best practices
5. 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 unitsand/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 LawPay Transparency Nondiscrimination Provision E-Verify