Career

How To Become A Machine Learning Engineer In North Carolina 2024

Learn everything you need to know about becoming a Machine Learning Engineer, including salary, schools, and programs.

Machine Learning Engineer in North Carolina Career Overview

As a Machine Learning Engineer, you will design, build, and deploy algorithms that enable computers to learn from and make decisions based on data. Your role is increasingly important in a variety of industries as organizations seek to leverage data for insights and strategic advantages.

Key responsibilities typically include:

  • Developing machine learning models by selecting appropriate algorithms and tuning their parameters.
  • Collaborating with data scientists and engineers to gather and preprocess data for analysis.
  • Conducting experiments to validate and improve model performance.
  • Implementing scalable solutions for deploying machine learning models in production environments.
  • Monitoring model performance over time and refining systems as needed.

The significance of a Machine Learning Engineer lies in their ability to translate complex data sets into actionable information. Your contributions will enhance automation, drive innovation, and improve decision-making processes across diverse applications such as healthcare, finance, marketing, and technology. As industries continue to embrace artificial intelligence, your expertise will be critical in shaping the future landscape of these sectors.

Best Schools to become a Machine Learning Engineer near North Carolina 2024

#1Prince George's County

University of Maryland-College Park

College Park, MD

In-State Tuition:$9,695
Out-of-State Tuition:$37,931
Admission Rate:45%
Graduation Rate:89%
Total Enrollment:40,792
#3Champaign County

University of Illinois Urbana-Champaign

Champaign, IL

In-State Tuition:$14,542
Out-of-State Tuition:$35,122
Admission Rate:45%
Graduation Rate:85%
Total Enrollment:56,916
#8Tompkins County

Cornell University

Ithaca, NY

In-State Tuition:$62,456
Out-of-State Tuition:$62,456
Admission Rate:7%
Graduation Rate:95%
Total Enrollment:25,898

Machine Learning Engineer Salary in North Carolina

Annual Median: $126,940
Hourly Median: $61.03

Data sourced from Career One Stop, provided by the BLS Occupational Employment and Wage Statistics wage estimates.

Required Education To Become a Machine Learning Engineer in North Carolina

To become a Machine Learning Engineer, you will typically need a strong educational background in one of the following fields:

  • Bachelor's Degree in Artificial Intelligence: This program focuses on the principles and applications of AI technologies, including machine learning algorithms, neural networks, and robotics.

  • Bachelor's Degree in Computer Science: A degree in computer science provides a solid foundation in programming, data structures, algorithms, and software development, all of which are essential for machine learning engineering.

  • Bachelor's Degree in Data Science: This program combines statistics, data analysis, and machine learning, equipping you with the necessary skills to manage and interpret complex data sets.

  • Bachelor's Degree in Computational and Applied Mathematics: This area of study emphasizes mathematical modeling and numerical analysis, providing key insights into how algorithms function within machine learning frameworks.

  • Bachelor's Degree in Applied Mathematics: A degree in applied mathematics prepares you for the theoretical aspects of machine learning through coursework in statistics, optimization, and mathematical modeling.

Advanced positions may require further education:

  • Master's Degree in Artificial Intelligence or Machine Learning: A master's program specializing in machine learning deepens your understanding of advanced algorithms, artificial intelligence application, and data-driven decision-making.

  • Master's Degree in Data Science: This program will enhance your analytical skills and knowledge of machine learning techniques used in real-world data applications.

  • Master's Degree in Computational and Applied Mathematics: Pursuing this degree allows you to explore sophisticated mathematical theories and their practical applications in machine learning.

  • Ph.D. in Artificial Intelligence, Machine Learning, or a related field: A doctoral program will provide you with in-depth research opportunities and advanced knowledge needed for high-level positions or academic roles in machine learning.

In addition to formal education, gaining hands-on experience through internships, projects, or research can greatly enhance your understanding and application of machine learning concepts.

Best Schools to become a Machine Learning Engineer near North Carolina 2024

#1Prince George's County

University of Maryland-College Park

College Park, MD

In-State Tuition:$9,695
Out-of-State Tuition:$37,931
Admission Rate:45%
Graduation Rate:89%
Total Enrollment:40,792
#3Champaign County

University of Illinois Urbana-Champaign

Champaign, IL

In-State Tuition:$14,542
Out-of-State Tuition:$35,122
Admission Rate:45%
Graduation Rate:85%
Total Enrollment:56,916
#8Tompkins County

Cornell University

Ithaca, NY

In-State Tuition:$62,456
Out-of-State Tuition:$62,456
Admission Rate:7%
Graduation Rate:95%
Total Enrollment:25,898
Machine Learning Engineer Job Description:
  • Develop and implement a set of techniques or analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualization software.
  • Apply data mining, data modeling, natural language processing, and machine learning to extract and analyze information from large structured and unstructured datasets.
  • Visualize, interpret, and report data findings.
  • May create dynamic data reports.

Machine Learning Engineer Required Skills and Competencies in North Carolina

  • Programming Languages: Proficiency in languages such as Python, R, and Java is essential. Python, in particular, is widely used in machine learning for its simplicity and the extensive libraries available.

  • Mathematics and Statistics: A solid understanding of linear algebra, calculus, probability, and statistics is important for developing algorithms and understanding data behaviors.

  • Machine Learning Frameworks: Familiarity with popular frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, and Keras will enhance your ability to design and implement machine learning models effectively.

  • Data Manipulation and Analysis: Skills in data manipulation tools like Pandas and NumPy are important for cleaning, transforming, and analyzing datasets to enable effective model training.

  • Algorithm Knowledge: Understanding various machine learning algorithms (e.g., regression, classification, clustering) and their applications helps in selecting the right approach for specific problems.

  • Model Evaluation and Tuning: Competency in evaluating model performance using metrics such as accuracy, precision, recall, and F1 score is crucial, along with skills in hyperparameter tuning to improve model effectiveness.

  • Big Data Technologies: Familiarity with big data platforms like Hadoop, Spark, or Kafka can be beneficial for handling large datasets that are common in machine learning applications.

  • Software Development Practices: Knowledge of version control systems like Git, and understanding software development lifecycles (SDLC), helps in maintaining code quality and collaboration in teams.

  • Data Visualization: Skills in data visualization tools such as Matplotlib, Seaborn, or Tableau are important for presenting insights and model results in a clear and meaningful way.

  • Cloud Computing Platforms: Experience with cloud services like AWS, Google Cloud, or Azure can significantly enhance your ability to deploy and scale machine learning applications.

  • Problem-Solving Skills: Strong analytical and critical thinking abilities will aid in formulating effective solutions to complex business problems using machine learning techniques.

  • Communication Skills: The capacity to communicate technical concepts to non-technical stakeholders is essential for ensuring that machine learning initiatives align with business objectives.

  • Collaboration and Teamwork: Working effectively in multidisciplinary teams, often alongside data scientists, business analysts, and software engineers, is key to successful project execution.

  • Continuous Learning: A commitment to ongoing education and staying updated with the latest advancements in machine learning, tools, and technologies ensures your skills remain relevant in a rapidly evolving field.

Job Duties for Machine Learning Engineers

  • Analyze, manipulate, or process large sets of data using statistical software.

  • Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.

  • Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.

Technologies Used by Machine Learning Engineers

Data base user interface and query software

  • Amazon Elastic Compute Cloud EC2
  • Amazon Redshift

Object or component oriented development software

  • C#
  • Scala

Presentation software

  • Microsoft PowerPoint

Job Market and Opportunities for Machine Learning Engineer in North Carolina

The job market for Machine Learning Engineers in North Carolina is dynamic and rapidly evolving, reflective of the broader trends seen across the tech industry. Here are key aspects of the current landscape:

  • Demand for Machine Learning Engineers: The demand for qualified Machine Learning Engineers is strong. Businesses spanning various sectors, including finance, healthcare, manufacturing, and technology, are increasingly leveraging machine learning to gain insights, optimize operations, and enhance customer experiences. This trend drives a steady need for skilled professionals in machine learning.

  • Growth Potential: The field is anticipated to experience significant growth over the next several years. As organizations continue to recognize the value of data-driven decision-making, the role of Machine Learning Engineers will become even more integral. With advancements in artificial intelligence and machine learning technologies, you're likely to find many opportunities for career advancement and specialization.

  • Geographical Hotspots: In North Carolina, several regions are emerging as key hotspots for machine learning opportunities:

    • Research Triangle: Comprising Raleigh, Durham, and Chapel Hill, the Research Triangle area is a hub for technology and research. Numerous tech companies, startups, and research institutions are based here, creating a rich ecosystem for Machine Learning Engineers.
    • Charlotte: Known primarily as a financial services center, Charlotte is seeing an increasing number of investments in fintech and analytics. This shift is pushing demand for machine learning expertise to enhance financial services and customer analytics.
    • Winston-Salem and Greensboro: These cities house a growing tech sector with a focus on healthcare and manufacturing industries that require machine learning solutions for process improvement and predictive analytics.

  • Industry Partnerships and Research Institutions: Collaborations between universities and industries are thriving in several North Carolina cities, providing avenues for research and application of machine learning. Institutions such as North Carolina State University and Duke University are engaged in cutting-edge AI research, contributing to a skilled talent pool in the region.

  • Remote Work Opportunities: The growth of remote work has further expanded your job prospects. Many companies nationwide are open to hiring remote Machine Learning Engineers, allowing you to work from North Carolina while being part of larger organizations based outside the state.

These elements reflect a vibrant job market for Machine Learning Engineers in North Carolina, characterized by expanding opportunities and a collaborative environment that fosters innovation and growth.

Top Related Careers to Machine Learning Engineer 2024

Data Visualization Specialist
Quantitative Analyst
Data Analyst
Business Intelligence Developer

Additional Resources To Help You Become a Machine Learning Engineer in North Carolina

  • Books

    • "Pattern Recognition and Machine Learning" by Christopher M. Bishop
      A foundational textbook covering various aspects of machine learning and pattern recognition.
    • "Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
      An essential resource that covers deep learning methods and their applications.
    • "Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow" by Aurélien Géron
      A practical guide focusing on implementing machine learning algorithms using popular Python libraries.

  • Online Courses

    • Coursera - Machine Learning by Andrew Ng
      A widely recognized introduction to machine learning, covering supervised and unsupervised learning concepts.
      Link to course
    • edX - Introduction to Artificial Intelligence (AI)
      A course that includes machine learning topics and their applications in AI.
      Link to course
    • Udacity - Machine Learning Engineer Nanodegree
      A specialized program focusing on practical skills needed for a career as a machine learning engineer.
      Link to program

  • Websites

    • Kaggle
      A platform for data science competitions and collaborative projects, offering datasets and notebooks for practice.
      Link to website
    • Towards Data Science
      A Medium publication featuring articles, tutorials, and guides on machine learning and data science.
      Link to website
    • TensorFlow
      The official website for TensorFlow, a popular open-source machine learning library with comprehensive documentation and tutorials.
      Link to website

  • Professional Organizations

    • Association for the Advancement of Artificial Intelligence (AAAI)
      A professional organization dedicated to advancing the scientific understanding of artificial intelligence.
      Link to organization
    • Institute of Electrical and Electronics Engineers (IEEE)
      A leading organization for advancing technology and providing resources in various engineering disciplines, including machine learning.
      Link to organization

  • Research and Academic Journals

    • Journal of Machine Learning Research (JMLR)
      An open-access journal that publishes research on machine learning techniques and applications.
      Link to journal
    • Nature Machine Intelligence
      A multidisciplinary journal covering the latest research in machine learning and its impact on society.
      Link to journal

  • Conferences and Workshops

    • Conference on Neural Information Processing Systems (NeurIPS)
      One of the leading conferences in machine learning and artificial intelligence that showcases cutting-edge research.
      Link to conference
    • International Conference on Machine Learning (ICML)
      A premier conference that brings together researchers and practitioners to discuss new advances in machine learning.
      Link to conference

Utilizing these resources will deepen your understanding and enhance your skills as a Machine Learning Engineer, positioning you well in this dynamic field.

Frequently Asked Questions (FAQs) About Machine Learning Engineer in North Carolina

  • What educational background is necessary to become a Machine Learning Engineer?
    You typically need a bachelor’s degree in computer science, data science, mathematics, or a related field. Many positions prefer candidates with a master's degree or Ph.D. in machine learning, artificial intelligence, or statistics.

  • What programming languages should I learn?
    Proficiency in Python is essential, as it is widely used in machine learning. Additionally, you may find it beneficial to learn R, Java, C++, or Scala, depending on the specific job requirements and projects.

  • What skills are important for a Machine Learning Engineer?
    Key skills include:

    • Strong understanding of algorithms and data structures
    • Experience with machine learning frameworks like TensorFlow, Keras, or PyTorch
    • Proficiency in data manipulation and analysis tools such as Pandas and NumPy
    • Knowledge of SQL and database management
    • Familiarity with cloud platforms (AWS, Azure, Google Cloud)

  • What is the job outlook for Machine Learning Engineers in North Carolina?
    The demand for machine learning engineers is growing rapidly due to increased adoption of AI technologies across various industries. North Carolina is home to a growing tech sector, particularly in cities like Raleigh and Charlotte, which is conducive to job growth in this field.

  • What industries hire Machine Learning Engineers?
    Machine Learning Engineers are in demand across numerous industries, including:

    • Technology and software development
    • Healthcare and biotech
    • Financial services
    • E-commerce and retail
    • Automotive and manufacturing

  • What are typical job responsibilities of a Machine Learning Engineer?
    Responsibilities generally include:

    • Designing and implementing machine learning models
    • Preprocessing and analyzing large datasets
    • Collaborating with data scientists, software engineers, and stakeholders
    • Conducting experiments to validate models and improving performance
    • Deploying models into production environments

  • How can I gain experience in machine learning?
    You can gain experience by:

    • Participating in internships or co-op programs
    • Engaging in online courses and certifications in machine learning
    • Working on personal projects or contributing to open-source projects
    • Joining local meetups or hackathons focused on AI and machine learning

  • What certifications may enhance my qualifications?
    Relevant certifications can enhance your profile, such as:

    • Google Professional Machine Learning Engineer
    • AWS Certified Machine Learning – Specialty
    • Microsoft Certified: Azure Data Scientist Associate

  • How much can I expect to earn as a Machine Learning Engineer in North Carolina?
    Salaries can vary based on experience, education, and specific location, but as of now, entry-level positions may start around $80,000 per year, while experienced engineers can earn upwards of $130,000 annually, and senior roles can exceed $150,000.

  • Is remote work an option for Machine Learning Engineers?
    Yes, many companies offer remote work options for Machine Learning Engineers, although the extent of these options may depend on the employer and the specific role.

  • What tools and software should I be familiar with?
    Familiarity with the following tools can be advantageous:

    • Version control systems (e.g., Git)
    • Data visualization tools (e.g., Tableau, Matplotlib)
    • Integrated Development Environments (IDEs) like Jupyter Notebook, PyCharm, or VSCode
    • Cloud-based machine learning services (e.g., AWS SageMaker, Google AI Platform)