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Full Time Machine Learning Finance Jobs in Raleigh, NC

This is a full-time position based in Raleigh, NC. (Hybrid - 3 days in office) About the Role We are seeking a Consultant-level Machine Learning Engineer to lead the implementation and scaling of AI ...

Provide technical leadership across machine learning, statistical modeling, feature engineering ... Partner with pricing, underwriting, actuarial, sales, finance, technology, data engineering, and ...

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We develop artificial intelligence and machine learning solutions that help the Department of ... Partner closely with finance staff to ensure budgets and cost volumes are accurate, compliant, and ...

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Full Time Machine Learning Finance information

See Raleigh, NC salary details

$24.3K

$90K

$131.7K

How much do full time machine learning finance jobs pay per year?

As of Jul 8, 2026, the average yearly pay for full time machine learning finance in Raleigh, NC is $90,045.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,900.00 and $106,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Full Time Machine Learning Finance professional, and why are they important?

To thrive as a Full Time Machine Learning Finance professional, you need a solid background in quantitative analysis, statistics, computer science, and finance, usually supported by a relevant degree. Proficiency with programming languages like Python or R, experience with machine learning frameworks (such as TensorFlow or scikit-learn), and familiarity with financial data systems are essential. Strong problem-solving abilities, attention to detail, and effective communication skills help you stand out in this field. These skills ensure the successful development and deployment of data-driven financial models that support better decision-making and risk management.

What is a Full Time Machine Learning Finance job?

A Full Time Machine Learning Finance job involves applying machine learning techniques and algorithms to financial data and problems. Professionals in this role develop predictive models for tasks such as risk assessment, trading strategies, fraud detection, and portfolio optimization. They work closely with financial analysts and data scientists to create solutions that can automate processes, improve decision-making, and identify patterns in large datasets. The role typically requires strong knowledge of both finance and advanced machine learning methods, as well as programming and data analysis skills.

What is the difference between Full Time Machine Learning Finance vs Full Time Data Scientist?

AspectFull Time Machine Learning FinanceFull Time Data Scientist
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of finance and machine learning certificationsDegree in Statistics, Computer Science, or related fields; data analysis and programming skills
Work EnvironmentFinancial institutions, hedge funds, banks, fintech companiesTech companies, consulting firms, finance, healthcare, retail
Industry UsageFinance-specific applications like risk modeling, algorithmic tradingBroad industry applications including marketing, healthcare, finance

Full Time Machine Learning Finance roles focus on applying machine learning techniques specifically to financial data and problems within financial institutions. In contrast, Full Time Data Scientist positions have a broader scope across various industries, utilizing data analysis and modeling skills to solve diverse business challenges. While both roles require strong technical skills, the finance-specific role emphasizes financial knowledge and applications.

What are some common challenges faced by machine learning professionals working in the finance sector?

Machine learning professionals in finance often encounter challenges such as dealing with sensitive and highly regulated data, ensuring model transparency and explainability for compliance purposes, and adapting to rapidly changing market conditions. Additionally, integrating machine learning models with existing financial systems and collaborating closely with domain experts, such as quantitative analysts and risk managers, are key parts of the role. Staying updated on both technological advancements and regulatory changes is also essential for success in this dynamic environment.
What are the most commonly searched types of Machine Learning Finance jobs in Raleigh, NC? The most popular types of Machine Learning Finance jobs in Raleigh, NC are:
What are popular job titles related to Full Time Machine Learning Finance jobs in Raleigh, NC? For Full Time Machine Learning Finance jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Full Time Machine Learning Finance jobs in Raleigh, NC look for? The top searched job categories for Full Time Machine Learning Finance jobs in Raleigh, NC are:
Machine Learning Engineer / MLOps Engineer

Machine Learning Engineer / MLOps Engineer

CGI Inc.

Raleigh, NC • On-site

Full-time

Retirement, PTO

Posted 16 days ago


CGI rating

7.1

Company rating: 7.1 out of 10

Based on 19 frontline employees who took The Breakroom Quiz

129th of 207 rated it services


Job description

Machine Learning Engineer / MLOps Engineer
Category: Software Development/ Engineering
Main location: United States, North Carolina, Raleigh
Alternate Location(s): United States, Louisiana, Lafayette
United States, Connecticut, Bloomfield
United States, Texas, Austin
Position ID:J0626-1399
Employment Type: Full Time
U.S. - The best version of me
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Position Description:
We CGI is seeking a highly motivated Machine Learning Engineer / MLOps Engineer to design, develop, deploy, and maintain scalable machine learning solutions in a cloud native environment. The ideal candidate will have hands on experience across the machine learning lifecycle, including model development, deployment, monitoring, and operationalization using AWS cloud services and modern MLOps practices.
This role requires strong expertise in machine learning engineering, backend service development, CI/CD automation, and cloud infrastructure. The candidate will collaborate with data scientists, software engineers, and business stakeholders to deliver production ready AI/ML solutions that drive business value.
This position can be located in Raleigh, NC (Preferred), Lafayette, LA, Bloomfield, CT, Austin, TX in a Hybrid Model.
Your future duties and responsibilities:
. Design, build, and maintain end to end machine learning pipelines and MLOps workflows.
. Develop, train, evaluate, and optimize machine learning models using Python and industry standard ML libraries.
. Implement model lifecycle management using MLflow, including experiment tracking, model registration, versioning, and deployment.
. Automate model deployment processes using CI/CD pipelines and GitHub Actions.
. Monitor deployed models for performance, drift, reliability, and operational health.
. Define and implement model performance metrics, monitoring dashboards, and alerting mechanisms.
. Develop and maintain RESTful APIs and backend services using FastAPI.
. Design scalable database schemas and data access layers using PostgreSQL and SQLAlchemy ORM.
. Deploy and manage containerized applications using Amazon ECS and Amazon ECR.
. Configure and manage cloud native services including Amazon API Gateway, Application Load Balancer (ALB), Amazon RDS, and Amazon S3.
. Collaborate with cross functional teams to ensure secure, scalable, and maintainable AI/ML solutions.
. Participate in code reviews, architecture discussions, and continuous improvement initiatives.
. Troubleshoot production issues and optimize application and infrastructure performance.
. Contribute to AI/ML platform enhancements and adoption of best practices across engineering teams.
Required qualifications to be successful in this role:
At least 3+years of hands on experience in Machine Learning Engineering or MLOps.
Strong experience with:
o MLflow for experiment tracking and model lifecycle management.
o Spark ML and distributed machine learning workflows.
o Python and ML libraries such as Scikit learn, Pandas, NumPy, TensorFlow, or PyTorch.
o Model training, evaluation, and performance optimization.
o Model registration, versioning, and lifecycle management.
o Production model deployment and CI/CD automation.
o Model monitoring, observability, and performance metrics tracking.
o GitHub Actions for build, deployment, and automation workflows.
AWS Cloud Services (2+ Years)
. Minimum 2 years of experience building and deploying applications on AWS.
Hands on experience with:
o Amazon ECS for container orchestration and application runtime.
o Amazon ECR for container image management.
o Amazon API Gateway for API publishing and routing.
o Amazon RDS for managed relational databases.
o Application Load Balancer (ALB) for traffic management and scaling.
o Amazon S3 for artifact management and object storage.
. Experience implementing secure, scalable, and highly available cloud architectures.
Backend Development (1+ Year)
. Minimum 1 year of backend application development experience.
Experience with:
o FastAPI based application and service development.
o REST API design, implementation, and documentation.
o SQL programming and relational database concepts.
o PostgreSQL database administration and optimization.
o SQLAlchemy and ORM based data modeling.
o Database schema design and relationship mapping.
Desired qualifications/non essential skills required:
Agentic AI
. Experience building AI agents, autonomous workflows, or multi agent systems.
. Familiarity with frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar technologies.
Databricks (2+ Years)
. Experience working with Databricks platform components, including:
o Unity Catalog for governance and data access management.
o Jobs and Workflows for orchestration and automation.
o Workspace and access management.
. Experience integrating Databricks with enterprise ML and data engineering workflows.
Education: Bachelor's degree in computer science or related field.
#LI-ARK1
CGI is required by law in some jurisdictions to include a reasonable estimate of the compensation range for this role. The determination of this range includes various factors not limited to skill set, level, experience, relevant training, and licensure and certifications. To support the ability to reward for merit-based performance, CGI typically does not hire individuals at or near the top of the range for their role. Compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range for this role in the U.S. is $80,600.00 $218,200.00.
CGI's benefits are offered to eligible professionals on their first day of employment to include:
. Competitive compensation
. Comprehensive insurance options
. Matching contributions through the 401(k) plan and the share purchase plan
. Paid time off for vacation, holidays, and sick time
. Paid parental leave
. Learning opportunities and tuition assistance
. Wellness and Well-being programs
Skills:
  • FastAPI
  • Amazon Web Services Cloud
  • Data Engineering
  • Data Engineering
  • Databricks
  • Machine Learning
  • Agentic AI
  • Continuous Integration
  • Postgre SQL
  • RESTful (Rest-APIs)
  • SQL

What you can expect from us:
Together, as owners, let's turn meaningful insights into action.
Life at CGI is rooted in ownership, teamwork, respect and belonging. Here, you'll reach your full potential because...
You are invited to be an owner from day 1 as we work together to bring our Dream to life. That's why we call ourselves CGI Partners rather than employees. We benefit from our collective success and actively shape our company's strategy and direction.
Your work creates value. You'll develop innovative solutions and build relationships with teammates and clients while accessing global capabilities to scale your ideas, embrace new opportunities, and benefit from expansive industry and technology expertise.
You'll shape your career by joining a company built to grow and last. You'll be supported by leaders who care about your health and well-being and provide you with opportunities to deepen your skills and broaden your horizons.
Come join our team-one of the largest IT and business consulting services firms in the world.
Qualified applicants will receive consideration for employment without regard to their race, ethnicity, ancestry, color, sex, religion, creed, age, national origin, citizenship status, disability, pregnancy, medical condition, military and veteran status, marital status, sexual orientation or perceived sexual orientation, gender, gender identity, and gender expression, familial status or responsibilities, reproductive health decisions, political affiliation, genetic information, height, weight, or any other legally protected status or characteristics to the extent required by applicable federal, state, and/or local laws where we do business.
CGI provides reasonable accommodations to qualified individuals with disabilities. If you need an accommodation to apply for a job in the U.S., please email the CGI U.S. Employment Compliance mailbox at US_Employment_Compliance@cgi.com. You will need to reference the Position ID of the position in which you are interested. Your message will be routed to the appropriate recruiter who will assist you. Please note, this email address is only to be used for those individuals who need an accommodation to apply for a job. Emails for any other reason or those that do not include a Position ID will not be returned.
We make it easy to translate military experience and skills! Click here to be directed to our site that is dedicated to veterans and transitioning service members.
All CGI offers of employment in the U.S. are contingent upon the ability to successfully complete a background investigation. Background investigation components can vary dependent upon specific assignment and/or level of US government security clearance held. Dependent upon role and/or federal government security clearance requirements, and in accordance with applicable laws, some background investigations may include a credit check. CGI will consider for employment qualified applicants with arrests and conviction records in accordance with all local regulations and ordinances.
CGI will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with CGI's legal duty to furnish information.

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