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Adaptive Ml Jobs in Raleigh, NC (NOW HIRING)

CoVar

Signal Processing Engineer

Durham, NC

RF signal processing, electronic warfare, optimization, array processing, machine learning, adaptive signal processing, AI/ML algorithm development, radar modeling, RF propagation * Ability to work ...

TMS

Robotics Automation Architect

Durham, NC · On-site

Hands-on experience orchestrating ML-integrated automation pipelines to deliver adaptive, intelligent workflows. ◉ UiPath Process Mining: Practical execution of large-scale process discovery ...

Varsity Tutors

Machine Learning Tutor

Chapel Hill, NC · Remote

$18 - $40/hr

Curriculum Awareness & Adaptive Instruction: Familiar with machine learning curricula and common ... based ML through advanced deep learning and deployment. * Effective Teaching Methods: Ability to ...

Varsity Tutors

Machine Learning Tutor

Durham, NC · Remote

$18 - $40/hr

Curriculum Awareness & Adaptive Instruction: Familiar with machine learning curricula and common ... based ML through advanced deep learning and deployment. * Effective Teaching Methods: Ability to ...

Varsity Tutors

Machine Learning Tutor

Raleigh, NC · Remote

$18 - $40/hr

Curriculum Awareness & Adaptive Instruction: Familiar with machine learning curricula and common ... based ML through advanced deep learning and deployment. * Effective Teaching Methods: Ability to ...

All JobsAdaptive Ml JobsAdaptive Ml Jobs in Raleigh, NC

Adaptive Ml information

See Raleigh, NC salary details

$40.8K

$99.6K

$145.8K

How much do adaptive ml jobs pay per year?

As of Aug 6, 2026, the average yearly pay for adaptive ml in Raleigh, NC is $99,579.00, according to ZipRecruiter salary data. Most workers in this role earn between $81,200.00 and $115,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an adaptive ML engineer?

To thrive as an Adaptive Machine Learning Engineer, you need strong foundations in machine learning algorithms, data analysis, and programming (often with a degree in computer science or a related field). Familiarity with ML frameworks (such as TensorFlow or PyTorch), version control systems, and cloud platforms is typically required, along with knowledge of adaptive and online learning techniques. Strong problem-solving abilities, creativity, and effective communication skills help you design, iterate, and implement adaptive models that respond to evolving data. These skills ensure that ML solutions can dynamically adjust to new information, maximizing their long-term effectiveness and impact.

What is an adaptive ML engineer?

An Adaptive ML Engineer is a professional who designs, develops, and maintains machine learning systems that can adjust and improve their performance dynamically in response to new data or changing environments. These engineers focus on creating algorithms and models that evolve over time, often using techniques like online learning, reinforcement learning, or continual learning. Their work is crucial in applications where static models are insufficient, such as real-time recommendations, autonomous vehicles, and personalized user experiences. Adaptive ML Engineers also ensure that their systems remain robust, accurate, and relevant as data patterns shift.

What are common challenges faced by professionals working in adaptive ML roles, and how can they overcome them?

Professionals in Adaptive Machine Learning often encounter challenges such as handling non-stationary data streams, ensuring model stability during continuous updates, and addressing concept drift where data patterns change over time. To overcome these, it's important to implement rigorous monitoring systems, use robust validation techniques, and collaborate closely with data engineering teams to ensure data quality. Staying up to date with the latest research and leveraging online learning frameworks can also help adapt models efficiently and maintain high performance.

What is adaptive machine learning?

Adaptive machine learning is a subset of machine learning where models automatically adjust their parameters or structure in response to new data or changing environments. This approach enables systems to improve performance over time without manual reprogramming, often involving techniques like online learning and continual learning. It is used in applications requiring real-time updates and dynamic decision-making.

What is the difference between Adaptive Ml vs Data Scientist?

AspectAdaptive MlData Scientist
Required CredentialsTypically a degree in Computer Science, Data Science, or related fields; knowledge of machine learning frameworksUsually a degree in Data Science, Statistics, Computer Science, or related fields; strong programming and statistical skills
Work EnvironmentTech companies, AI startups, research labs focusing on machine learning applicationsVaried environments including tech firms, finance, healthcare, and consulting firms analyzing data for insights
Employer & Industry UsageUsed in industries developing adaptive machine learning models and AI solutionsUsed across industries for data analysis, predictive modeling, and decision support

Adaptive ML specialists focus on developing and implementing machine learning models that adapt over time, often working on AI systems. Data Scientists analyze data, build models, and generate insights. While both roles require strong technical skills, Adaptive ML roles are more specialized in creating adaptive algorithms, whereas Data Scientists focus on broader data analysis and modeling tasks.

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Adaptive Ml jobs near you

Signal Processing Engineer

CoVar

Durham, NC

Full-time

Re-posted 2 days ago

Job description

Signal Processing Engineer

About CoVar

CoVar is a small AI/ML R&D software company in Durham, NC, that uses artificial intelligence to solve problems that matter. We develop AI/ML tools to help the DoD detect enemies and threats, help biomedical researchers find new cures for diseases, and help monitor machinery to prevent injuries and environmental catastrophes. We are passionate engineers, dedicated to pushing the bounds of what AI/ML can do in the real world.

About this position

You will help CoVar develop signal processing algorithms and software to solve real-world customer problems. You will develop novel and advanced algorithms for sense making and sensor decision making for applications in the RF domain to include detection, localization, classification, tracking and EW. You will design and implement simulations for these RF applications as well as evaluate results on real world data. You will have the opportunity to present your work to high-level customers in the DoD and in the industry. The position includes opportunities to publish novel work in both classified and unclassified settings.

Key Responsibilities

  • Algorithm Development: Design, implement, and optimize signal and array processing algorithms for RF applications, detection, localization, tracking, channel estimation, beamforming, and spectral analysis.
  • Data Analysis: Process and interpret RF datasets for signal detection, classification, tracking, parameter estimation, and pattern recognition.
  • Prototyping & Testing: Develop simulation models (e.g., Python, MATLAB) and implement algorithms on real-time platforms such as FPGAs, GPUs, or SDRs (Software-Defined Radios).
  • RF System Integration: Collaborate with hardware engineers to integrate digital signal processing (DSP) algorithms into RF systems and ensure optimal end-to-end performance.
  • Performance Evaluation: Conduct laboratory and field testing to validate system performance under various operational conditions.
  • Research & Innovation: Stay up to date with emerging RF technologies, advanced signal processing techniques, and industry best practices.
  • Documentation: Prepare technical reports and presentations for internal and external stakeholders.

Minimum qualifications

  • B.S., M.S., or Ph.D in Electrical Engineering, Computer Engineering, Applied Physics, Applied Mathematics, or a related field.
  • 3+ years of experience in RF signal processing or a related discipline.
  • Strong proficiency in one or more of the following programming languages: Python, C/C++, or MATLAB.
  • Experience in the following areas:
    • RF signal processing, electronic warfare, optimization, array processing, machine learning, adaptive signal processing, AI/ML algorithm development, radar modeling, RF propagation
  • Ability to work with cross-functional engineering teams and clearly communicate complex technical concepts.
  • Ability to work in Durham, NC (relocation assistance available)
  • Eligibility for US security clearance

Preferred qualifications

  • Experience with:
    • Radar signal processing in Department of Defense (DoD) specific applications including electronic warfare (EW) techniques such as electronic support measures, attack, protection, and cognitive EW.
    • AI/ML algorithm design in the areas of computer vision, reinforcement learning (RL), and natural language processing.
    • Spectrum monitoring and signal classification using machine learning techniques.
    • Translating the mission needs of DoD customers into an end-to-end technical solution.
    • Proposal development and proposal writing.
  • Familiarity with FPGA or GPU acceleration for high-performance DSP.
  • Proficiency in C/C++ for embedded or real-time applications.
  • Active U.S. security clearance.

Benefits

  • Competitive salary, cash bonus, equity structure, and 401k with employer contributions
  • Excellent health care coverage, including dental and vision plans
  • Parental leave
  • Short-term and long-term disability insurance
  • Life insurance
  • Flexible work schedule
  • Tuition support
  • PTO and paid holidays

Visit us: www.covar.com