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Ml Model Fine Tuning Jobs in Raleigh, NC (NOW HIRING)

First Citizens Bank

Principal AI Architect

Raleigh, NC

$160K - $240K/yr

... ML, feature stores, model monitoring, and drift detection. * Define enterprise patterns for training, fine-tuning, deployment, and observability of ML and GenAI workloads. * Guide teams on ...

First Citizens Bank

Principal AI Architect

Raleigh, NC

$160K - $240K/yr

... ML, feature stores, model monitoring, and drift detection. * Define enterprise patterns for training, fine-tuning, deployment, and observability of ML and GenAI workloads. * Guide teams on ...

GEI Consultants

AI Engineer

Cary, NC · On-site

... Models (LLMs), including solution development and fine-tuning for domain-specific tasks ... Prior experience implementing AI/ML solutions in professional services, engineering, or ...

GEI Consultants

AI Engineer

Cary, NC

$110K - $150K/yr

... Models (LLMs), including solution development and fine-tuning for domain-specific tasks ... Prior experience implementing AI/ML solutions in professional services, engineering, or ...

Qualcomm

Machine Learning Compiler

Raleigh, NC · On-site

... tuning across diverse ML models and hardware targets. • Manage and mentor a team of engineers, fostering technical growth and collaboration. • Plan and execute projects to meet release ...

Northern Base

AI Solution Lead

Cary, NC · On-site

... ML models for real-time and batch inference ✔ Hands-on experience with Kubernetes, Helm ... tuning, and data engineering best practices ✔ Experience collaborating with cross-functional ...

Accenture

Utilities Technical Lead

Raleigh, NC · On-site

$73K - $218K/yr

... model fine-tuning, evaluation frameworks, AI-powered automation, predictive monitoring, and intelligent document processing. Travel may be required for this role. The amount of travel will vary from ...

Deloitte

Senior Forward Deployed Engineer- AWS

Raleigh, NC

$101K - $139K/yr

... model monitoring, and prompt management * Experience with SageMaker fine-tuning (SFT and RFT) for ... Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science ...

Deloitte

Lead Forward Deployed Engineer - AWS

Raleigh, NC

$99K - $131K/yr

... model monitoring, and prompt management * Experience with SageMaker fine-tuning (SFT and RFT) for ... Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science ...

Deloitte

Forward Deployed Engineer- AWS

Raleigh, NC

... model monitoring, and prompt management * Experience with SageMaker fine-tuning (SFT and RFT) for ... Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science ...

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All JobsMl Model Fine Tuning JobsMl Model Fine Tuning Jobs in Raleigh, NC

Ml Model Fine Tuning information

See Raleigh, NC salary details

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How much do ml model fine tuning jobs pay per hour?

As of Aug 12, 2026, the average hourly pay for ml model fine tuning in Raleigh, NC is $67.40, according to ZipRecruiter salary data. Most workers in this role earn between $55.14 and $74.76 per hour, depending on experience, location, and employer.

What is the difference between Ml Model Fine Tuning vs Data Scientist?

AspectMl Model Fine TuningData Scientist
CredentialsKnowledge of machine learning frameworks, programming skillsDegree in data science, statistics, or related fields
Work EnvironmentFocus on model optimization, coding, and experimentationData analysis, modeling, and interpretation
Industry UsageAI/ML development teams, tech companiesResearch, analytics, business intelligence

While Ml Model Fine Tuning involves adjusting pre-trained models to improve performance, Data Scientists analyze data, develop models, and interpret results. Fine tuning is a specialized task within the broader scope of a Data Scientist's role, often requiring similar technical skills but focusing more on model optimization.

What are some common challenges faced when fine-tuning machine learning models in a production environment?

One common challenge when fine-tuning ML models in production is ensuring that the updated models generalize well to new, unseen data without overfitting to recent trends or noise. Additionally, coordinating with data engineers and software developers is crucial to maintain data pipelines and model deployment workflows. Managing computational resources and keeping track of model versions for reproducibility can also be complex, especially in fast-paced or large-scale environments. Regular communication with stakeholders is important to align model updates with business objectives and to ensure the smooth integration of improvements.

What is ML model fine-tuning?

ML model fine-tuning is the process of taking a pre-trained machine learning model and making small adjustments to its parameters using new data relevant to your specific task. This approach allows you to leverage the general knowledge the model has already learned, while adapting it to perform better on your particular dataset or problem. Fine-tuning is common in fields like natural language processing and computer vision, as it saves time and resources compared to training a model from scratch. The process typically involves retraining the last few layers of the model or using a lower learning rate for the entire model.

What are the key skills and qualifications needed to thrive as an ML model fine tuning specialist, and why are they important?

To thrive as an ML Model Fine Tuning Specialist, you need a solid background in machine learning, statistics, programming (often Python), and experience with model training and evaluation. Familiarity with frameworks such as TensorFlow, PyTorch, and tools like Hugging Face Transformers, along with experience in managing GPUs and cloud platforms, is typically required. Strong problem-solving skills, attention to detail, and effective communication help you understand project requirements and collaborate with data scientists and engineers. These skills are crucial for optimizing model performance, ensuring accurate results, and delivering robust AI solutions tailored to specific business needs.
What are popular job titles related to Ml Model Fine Tuning jobs in Raleigh, NC? For Ml Model Fine Tuning jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Ml Model Fine Tuning jobs in Raleigh, NC look for? The top searched job categories for Ml Model Fine Tuning jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Ml Model Fine Tuning jobs? Cities near Raleigh, NC with the most Ml Model Fine Tuning job openings:
Ml Model Fine Tuning jobs near you
Infographic showing various Ml Model Fine Tuning job openings in Raleigh, NC as of July 2026, with employment types broken down into 58% Full Time, and 42% Contract. Highlights an 49% In-person, and 51% Remote job distribution, with an average salary of $140,186 per year, or $67.4 per hour.

Principal Applied AI Engineer, Finance

Genesys

Durham, NC

Full-time

Medical, Dental, Vision, Retirement

Re-posted 27 days ago

Job description

Be the one building AI-powered experiences where they matter most.

At Genesys, we help organizations create better customer experiences through AI-powered experience orchestration. Our platform connects people, systems, data and AI to help organizations deliver more personalized service, improve operational efficiency and build stronger customer relationships.

Help build, support and operate technology used by more than 8,000 organizations in over 100 countries - moving AI from possibility to production in real-world enterprise environments every day.


Principal Applied AI Engineer, Finance

We are seeking a Principal Applied AI Engineer to lead the design and delivery of next-generation AI and predictive models that transform financial decision-making at scale. This role sits at the intersection of advanced machine learning, agentic AI, and software engineering, with a strong focus on production-grade AI systems, intelligent automation, and predictive modeling.

The ideal candidate is both a strategic technical leader and hands-on builder-capable of architecting complex AI systems with a software engineering mindset, influencing organizational direction, and delivering measurable business impact. You will drive innovation in Generative AI, lead the evolution toward agentic AI systems, and establish best practices across modeling, deployment, and governance in a finance context.

Key ResponsibilitiesAgentic AI & Generative Systems

  • Architect and lead the development of agentic AI systems that automate and augment finance workflows (e.g., forecasting, reporting, and decision support).

  • Design and implement multi-agent systems leveraging LLMs, tool-use frameworks, and orchestration patterns (e.g., RAG, model chaining, dynamic prompting).

  • Translate cutting-edge research in LLMs and agentic AI into scalable, production-ready solutions.

  • Establish guardrails, evaluation frameworks, and responsible AI practices to ensure safe, compliant, and reliable outputs.

  • Design fault-tolerant, observable agent systems with clear failure modes and recovery strategies

Predictive Modeling & Customer Behavior Forecasting

  • Lead the design and implementation of advanced predictive models, including time series forecasting and attrition prediction across customer segments.

  • Develop interpretable, production-grade models that drive retention strategies and financial planning.

  • Define and standardize evaluation metrics, validation frameworks, and monitoring systems for model performance and drift detection.

  • Translate complex predictive insights into actionable recommendations for finance and business leaders.

Software Engineering & AI System Architecture

  • Design and build scalable AI/ML systems with a strong emphasis on software engineering best practices (modular design, APIs, CI/CD, testing).

  • Lead end-to-end development from concept to production, ensuring robustness, scalability, and maintainability.

  • Develop and integrate AI services into internal applications and workflows, including light front-end/back-end components where needed.

  • Drive adoption of modern tooling (e.g., containerization, orchestration, cloud-native architectures).

Operationalization & Model Lifecycle Leadership

  • Establish and enforce MLOps best practices for deployment, monitoring, retraining, and governance of AI systems.

  • Ensure systems meet enterprise standards for security, compliance (e.g., SOX), and auditability.

  • Develop advanced feature engineering strategies capturing behavioral, financial, and temporal signals.

Technical Leadership & Strategy

  • Set technical direction for AI/ML initiatives across the finance organization.

  • Lead complex, cross-functional projects and mentor other data specialists.

  • Work alongside stakeholders across finance, IT, and product to adopt AI-driven solutions.

  • Contribute to long-term AI strategy, identifying opportunities to drive efficiency and innovation.

Key Qualifications

  • 8+ years of experience in data science, software engineering, and AI engineering, with significant experience deploying production systems.

  • Proven track record of building production AI systems used at scale.

  • Deep expertise in predictive modeling, including time series forecasting and customer churn modeling.

  • Advanced proficiency in Python and strong experience with ML/AI frameworks and system design.

  • Hands-on experience with LLMs, including prompt engineering, fine-tuning, and evaluation techniques.

  • Strong experience with cloud platforms (preferably AWS), distributed systems, and MLOps practices.

  • Experience working with financial data and compliance-aware modeling.

  • Strong software engineering foundation, including API development, containerization (Docker/Kubernetes), and CI/CD pipelines.

What Sets You Apart

  • Expertise in building production agentic AI frameworks, including multi-agent orchestration, tool-using agents, and autonomous workflows.

  • Experience building RAG-based systems, vector databases, and semantic search architectures.

  • Demonstrated ability to lead large-scale AI initiatives and influence technical strategy.

  • Deep understanding of responsible AI practices, including model alignment, guardrails, and bias mitigation.

  • Exceptional communication skills, with the ability to translate complex technical concepts into business value.

  • Track record of mentoring and elevating technical teams in high-impact environments.

Compensation:

This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate's experience, qualifications, skills, and location. This role might also be eligible for a commission or performance-based bonus opportunities.

$193,600.00 - $340,600.00

Benefits:

  • Medical, Dental, and Vision Insurance.

  • Telehealth coverage

  • Flexible work schedules and work from home opportunities

  • Development and career growth opportunities

  • Open Time Off in addition to 10 paid holidays

  • 401(k) matching program

  • Adoption Assistance

  • Fertility treatments

Click here to view a summary overview of our Benefits.


Working at Genesys

  • AI at enterprise scale- Build, support and operate AI-powered technology used by more than 8,000 organizations worldwide. 150+new AI features were released in the last fiscal year.
  • A flexible-first culture - Join a global team of nearly 7,000 employees with flexible ways of working designed to help people do their best work.
  • Growth in the AI era - Build future-ready skills through mentorship, learning programs, leadership development and education support.
  • Time to recharge and give back - Benefits include paid volunteer time, August Free Fridays, well-being resources and regionally tailored programs for employees and their families.
  • Recognized globally - Genesys is Great Place to Work certified in 17 countries and 94% of employees are proud to tell others they work at Genesys.

Learn more about our culture, AI innovation and sustainability commitments through our Careers site and Sustainability Report.


What Happens After You Apply

After you apply, here's what you can typically expect:

  • Our Talent Acquisition team reviews your application with the hiring team.
  • A Talent Acquisition Partner will review your application and, if your background is aligned, schedule a Zoom interview.
  • Next, you'll meet the hiring manager and other members of the interview team.
  • We aim to keep the process focused and respectful of your time, with no more than five interviews in most cases.
  • After interviews are complete, our team will follow up with the final steps.

Every application is reviewed by a person. Response times may vary by role and location, but our team will keep you informed throughout the process.


Stay Connected

Stay connected to learn more about how we're applying AI to customer and employee experience challenges and get notified when relevant opportunities become available.

Get notified about relevant opportunities.


Be the one building what's next - where AI, experience and impact come together.

Employee Referral

If a Genesys employee referred you, please apply using the link they shared so we can connect your application to their referral.


About Genesys:

Genesys empowers more than 8,000 organizations worldwide to create the best customer and employee experiences. With agentic AI at its core, Genesys Cloud is the AI-Powered Experience Orchestration platform that connects people, systems, data and AI across the enterprise. As a result, organizations can drive customer loyalty, growth and retention while increasing operational efficiency and teamwork across human and AI workforces. To learn more, visitwww.genesys.com.


Reasonable Accommodations:

If you require a reasonable accommodation to complete any part of the application process, or are limited in your ability to access or use this online application and need an alternative method for applying, you or someone you know may contact us at reasonable.accommodations@genesys.com.


You can expect a response within 24-48 hours. To help us provide the best support, click the email link above to open a pre-filled message and complete the requested information before sending. If you have any questions, please include them in your email.

This email is intended to support job seekers requesting accommodations. Messages unrelated to accommodation-such as application follow-ups or resume submissions-may not receive a response.


Genesys is an equal opportunity employer committed to fairness in the workplace. We evaluate qualified applicants without regard to race, color, age, religion, sex, sexual orientation, gender identity or expression,marital status, domestic partner status,national origin, genetics, disability,military andveteran status, and other protected characteristics.


Please note that recruiters will never ask for sensitive personal or financial information during the application phase.

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