1

Machine Learning Engineer Jobs in Cary, NC (NOW HIRING)

Senior AI Engineer - SFL Scientific

Raleigh, NC · On-site

$101K - $139K/yr

Work You'll Do As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...

CI Infrastructure Engineer

Raleigh, NC · On-site

$76K - $102K/yr

Engineering Group, Engineering Group > Machine Learning Engineering General Summary: We are looking for an experienced CI Infrastructure Engineer to own and evolve the continuous integration (CI ...

Software Engineer About CoVar CoVar is a small, mission-driven AI/ML R&D software company based in ... We build advanced software and machine learning systems that help the Department of Defense detect ...

We are looking for aMLOps Engineerto join our team and contribute to developing robust data solutionsto support our Machine Learning,Data Science, Data Engineering and Software Engineering. Position ...

Senior Google CX Engineer (GECX)

Durham, NC · On-site +1

$116K - $146K/yr

Active Google Cloud Professional Certifications such as Professional Cloud Architect, Professional Machine Learning Engineer, or Professional Data Engineer. * Practical expertise with Google Customer ...

We are looking for a MLOps Engineer to join our team and contribute to developing robust data solutions to support our Machine Learning, Data Science, Data Engineering and Software Engineering.

Lead AI/ML Engineer - Remote

Raleigh, NC · On-site +1

$99K - $131K/yr

The engineer applies deep learning technologies to enable computers to visualize, learn, and ... Develop and implement AI and machine learning strategies across several healthcare domains

CTIO AI Engineering Manager

Raleigh, NC · On-site

$73K - $244K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Participate in developing models using statistical or machine learning techniques and collaborate ... Prompt engineering & prompt chaining * Conversational AI design patterns * Strong programming ...

Senior Vision Software Engineer

Raleigh, NC · On-site

$119K - $157K/yr

Develop and implement machine learning derived software to solve business problems. * Integrate ... Mentor junior software developers and provide guidance on best practices and advanced analytical ...

CI Infrastructure Engineer

Raleigh, NC · On-site

$76K - $102K/yr

Qualcomm Technologies, Inc. is seeking an experienced CI Infrastructure Engineer to own and evolve the continuous integration infrastructure that supports their Machine Learning compiler stack. The ...

NGA AI Engineer Manager

Raleigh, NC · On-site

$73K - $244K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

DevOps Engineer

Raleigh, NC · On-site

$51.25 - $70.25/hr

... s Engineer Location: Raleigh, North Carolina, USA, remote till covid. * 2-3 years pf experience ... UiPath, Blue Prism, PEGA), SQL, GIT, Docker, OpenShift/Kubernetes, Machine Learning based document ...

next page

Showing results 1-20

Machine Learning Engineer information

See Cary, NC salary details

$29.2K

$119.3K

$179.3K

How much do machine learning engineer jobs pay per year?

As of Jul 15, 2026, the average yearly pay for machine learning engineer in Cary, NC is $119,293.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,000.00 and $143,600.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What is the difference between Machine Learning Engineer vs Data Scientist?

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Cary, NC? The most popular types of Machine Learning Engineer jobs in Cary, NC are:
What are popular job titles related to Machine Learning Engineer jobs in Cary, NC? For Machine Learning Engineer jobs in Cary, NC, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Cary, NC look for? The top searched job categories for Machine Learning Engineer jobs in Cary, NC are:
What cities near Cary, NC are hiring for Machine Learning Engineer jobs? Cities near Cary, NC with the most Machine Learning Engineer job openings:
Infographic showing various Machine Learning Engineer job openings in Cary, NC as of July 2026, with employment types broken down into 100% Full Time. Highlights an 50% Hybrid, and 50% Remote job distribution, with an average salary of $119,293 per year, or $57.4 per hour.
Senior AI Engineer - SFL Scientific

Senior AI Engineer - SFL Scientific

Deloitte

Raleigh, NC • On-site

$101K - $139K/yr

Other

Re-posted 26 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 90 frontline employees who took The Breakroom Quiz

60th of 148 rated financial services


Job description

Our Deloitte Strategy & Transactions team helps guide clients through their most critical moments and transformational initiatives. From strategy to execution, this team delivers integrated, end-to-end support and advisory services covering valuation modeling, cost optimization, restructuring, business design and transformation, infrastructure and real estate, mergers and acquisitions (M&A), and sustainability. Work alongside clients every step of the way, helping them navigate new challenges, avoid financial pitfalls, and provide practical solutions at every stage of their journey-before, during, and after any major transformational projects or transactions.
Are you eager to shape the future of emerging technologies? Imagine joining an acclaimed team where career paths span from account executives and data scientists to AI strategists, machine learning specialists, and data engineers. SFL Scientific, a Deloitte Business, is looking to add a Senior AI Engineer to their vibrant environment. SFL Scientific is part of our broader Strategy Offering within the Strategy & Transactions practice, whose specialized team brings together key capabilities to design integrated solutions that drive transformational change for our clients. Take the next step in your technical journey-develop your leadership, consulting acumen, and reputation as a trailblazer within the AI engineering field by joining our team!

Recruiting for this role ends on 8/31/2026.

Work You'll Do
As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and deployment services for our novel machine learning applications. Key to this role is the ability to demonstrate both traditional data engineering expertise, leveraging cloud/enterprise/open-source solutions, and constructing IT infrastructure for organizations across a wide variety of industries.

In our consultative approach, we are platform agnostic and committed to providing the best technical solutions for each client and solution. Our engineering team leverages emerging technologies and best practices across data security, documentation, cloud services and engineering architecture to create solutions and products that address complex issues and business problems faced by global organizations. Some of our novel use cases include cancer detection, drug discovery, optimizing population health and clinical trials, autonomous systems and edge AI, and renewable energy. Key responsibilities:

  • Work with clients to design, develop, and deploy new architectures to support machine learning & automation applications
  • Leverage advanced technical skills in modern data architecture, data science engineering, data transformation, and management of structured and unstructured data sources using cloud computing or on-prem technologies
  • Design and lead development on scalable, high-performance data architecture solutions that supports both the client business as well as AI/GenAI use cases
  • Support and enhance data architecture, and data pipelines, and define database schemas (Graph, SQL, NoSQL) to develop algorithm scalability and deployment based on agile business priorities and initiatives
  • Participate in architectural and deployment discussions to ensure solutions are designed for successful scale, security, and high availability in the cloud or on prem
  • Adopt best engineering practices in automation, HPC and AI/GenAI infrastructure and design patterns
  • Define and lead technology proof of concepts to ensure feasibility of new data and cloud technology solutions
  • Display strong thought leadership and execution in pursuit of modern data architecture principles and technology modernization
  • Mentor, motivate, and coach junior members on technical best practices and inspire professional development

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The Team

Our Strategy offering architects bold strategies to achieve business and mission goals, enabling growth, competitive advantage, technology modernization, and continuous digital and AI transformation.
Specifically, SFL Scientific, a Deloitte Business, is a data science professional services practice focused on strategy, technology, and solving business challenges with Artificial Intelligence (AI). The team has a proven track record serving large, market-leading organizations in the private and public sectors, successfully delivering high-quality, novel and complex projects, and offering deep domain and scientific capabilities. Made up of experienced AI strategists, data scientists, and AI engineers, they serve as trusted advisors to executives, helping them understand and evaluate new and essential areas for AI investment and identify unique opportunities to transform their businesses.
Qualifications

Required:

  • Bachelor's degree in a STEM field (Computer Science, Engineering, Physics, etc.) or equivalent experience
  • 4+ years of experience working in data engineering, data science, software engineering, MLOps specializing in AI and Machine Learning deployment
  • 4+ years of experience in designing cloud solutions and supporting production projects, including hands-on experience with AWS services (or Azure, GCP equivalents)
  • 4+ years of programming experience with Linux Shell/CLI, Python, SQL, PowerShell, etc.
  • 2+ years of experience managing teams in technical delivery and delivering complex and critical projects
  • 2+ years of experience in DevOps and leveraging CI/CD services: Puppet, Ansible, Chef, Airflow, Terraform, Jenkins
  • 2+ years of experience with database development and ETL/ELT pipelines (relational, NoSQL, Neo4j)
  • 2+ years of experience with deployment and optimization: Kubernetes, Docker, NVIDIA TensorRT/Triton, RAPIDs, Kubeflow, MLflow, Kafka, etc.
  • Live within commuting distance to one of Deloitte's consulting offices
  • Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred:

  • Master's degree in Computer Science, Engineering, Physics, etc. or related STEM field
  • AWS/Azure Certifications (AWS/Azure Certified: SysOps Administrator, DevOps Engineer, Solutions Architect)
  • 2+ years of experience with GPU computing (CUDA, OpenCL) and HPC system software stack

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $128,000 to $252,500.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Qualifications:

Our Deloitte Strategy & Transactions team helps guide clients through their most critical moments and transformational initiatives. From strategy to execution, this team delivers integrated, end-to-end support and advisory services covering valuation modeling, cost optimization, restructuring, business design and transformation, infrastructure and real estate, mergers and acquisitions (M&A), and sustainability. Work alongside clients every step of the way, helping them navigate new challenges, avoid financial pitfalls, and provide practical solutions at every stage of their journey-before, during, and after any major transformational projects or transactions.
Are you eager to shape the future of emerging technologies? Imagine joining an acclaimed team where career paths span from account executives and data scientists to AI strategists, machine learning specialists, and data engineers. SFL Scientific, a Deloitte Business, is looking to add a Senior AI Engineer to their vibrant environment. SFL Scientific is part of our broader Strategy Offering within the Strategy & Transactions practice, whose specialized team brings together key capabilities to design integrated solutions that drive transformational change for our clients. Take the next step in your technical journey-develop your leadership, consulting acumen, and reputation as a trailblazer within the AI engineering field by joining our team!

Recruiting for this role ends on 8/31/2026.

Work You'll Do
As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and deployment services for our novel machine learning applications. Key to this role is the ability to demonstrate both traditional data engineering expertise, leveraging cloud/enterprise/open-source solutions, and constructing IT infrastructure for organizations across a wide variety of industries.

In our consultative approach, we are platform agnostic and committed to providing the best technical solutions for each client and solution. Our engineering team leverages emerging technologies and best practices across data security, documentation, cloud services and engineering architecture to create solutions and products that address complex issues and business problems faced by global organizations. Some of our novel use cases include cancer detection, drug discovery, optimizing population health and clinical trials, autonomous systems and edge AI, and renewable energy. Key responsibilities:

  • Work with clients to design, develop, and deploy new architectures to support machine learning & automation applications
  • Leverage advanced technical skills in modern data architecture, data science engineering, data transformation, and management of structured and unstructured data sources using cloud computing or on-prem technologies
  • Design and lead development on scalable, high-performance data architecture solutions that supports both the client business as well as AI/GenAI use cases
  • Support and enhance data architecture, and data pipelines, and define database schemas (Graph, SQL, NoSQL) to develop algorithm scalability and deployment based on agile business priorities and initiatives
  • Participate in architectural and deployment discussions to ensure solutions are designed for successful scale, security, and high availability in the cloud or on prem
  • Adopt best engineering practices in automation, HPC and AI/GenAI infrastructure and design patterns
  • Define and lead technology proof of concepts to ensure feasibility of new data and cloud technology solutions
  • Display strong thought leadership and execution in pursuit of modern data architecture principles and technology modernization
  • Mentor, motivate, and coach junior members on technical best practices and inspire professional development

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The Team

Our Strategy offering architects bold strategies to achieve business and mission goals, enabling growth, competitive advantage, technology modernization, and continuous digital and AI transformation.
Specifically, SFL Scientific, a Deloitte Business, is a data science professional services practice focused on strategy, technology, and solving business challenges with Artificial Intelligence (AI). The team has a proven track record serving large, market-leading organizations in the private and public sectors, successfully delivering high-quality, novel and complex projects, and offering deep domain and scientific capabilities. Made up of experienced AI strategists, data scientists, and AI engineers, they serve as trusted advisors to executives, helping them understand and evaluate new and essential areas for AI investment and identify unique opportunities to transform their businesses.
Qualifications

Required:

  • Bachelor's degree in a STEM field (Computer Science, Engineering, Physics, etc.) or equivalent experience
  • 4+ years of experience working in data engineering, data science, software engineering, MLOps specializing in AI and Machine Learning deployment
  • 4+ years of experience in designing cloud solutions and supporting production projects, including hands-on experience with AWS services (or Azure, GCP equivalents)
  • 4+ years of programming experience with Linux Shell/CLI, Python, SQL, PowerShell, etc.
  • 2+ years of experience managing teams in technical delivery and delivering complex and critical projects
  • 2+ years of experience in DevOps and leveraging CI/CD services: Puppet, Ansible, Chef, Airflow, Terraform, Jenkins
  • 2+ years of experience with database development and ETL/ELT pipelines (relational, NoSQL, Neo4j)
  • 2+ years of experience with deployment and optimization: Kubernetes, Docker, NVIDIA TensorRT/Triton, RAPIDs, Kubeflow, MLflow, Kafka, etc.
  • Live within commuting distance to one of Deloitte's consulting offices...

What Deloitte employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom