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Signal Processing Machine Learning Jobs in North Carolina

Bespoke Labs

Machine Learning Engineer

Greenville, NC · On-site

This means designing observation spaces, action spaces, reward signals, and success criteria for ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

Bespoke Labs

Machine Learning Engineer

Charlotte, NC · On-site

This means designing observation spaces, action spaces, reward signals, and success criteria for ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

Bespoke Labs

Machine Learning Engineer

Elon, NC · On-site

This means designing observation spaces, action spaces, reward signals, and success criteria for ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

Bespoke Labs

Machine Learning Engineer

High Point, NC · On-site

This means designing observation spaces, action spaces, reward signals, and success criteria for ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

Bespoke Labs

Machine Learning Engineer

Durham, NC · On-site

This means designing observation spaces, action spaces, reward signals, and success criteria for ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

Bespoke Labs

Machine Learning Engineer

Wilmington, NC · On-site

This means designing observation spaces, action spaces, reward signals, and success criteria for ... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ...

Teladoc

Senior Machine Learning Scientist

Concord, NC · On-site +1

This is an opportunity to apply technical rigor, scalable data processing tools, and machine learning algorithms to solve real-world business problems while engineering, deploying, measuring, and ...

CRC Group

Machine Learning Engineer

Charlotte, NC · On-site

$140 - $180/hr

## Machine Learning EngineerApplylocations: Charlotte NC - 600 S Tryon St.: Morrisville NC, 3015 ... Help establish processes, tools, and standards for a growing ML team.* Mentor future hires and ...

Vadum Inc.

DSP Engineer with Security Clearance

Raleigh, NC · On-site

$127K - $149K/yr

... signal processing, information theory, probability/statistics, estimation/detection, pattern recognition, optimization, image processing, and machine vision. Experience with machine learning ...

Vadum Inc

DSP Engineer

Raleigh, NC · On-site

$125K - $180K/yr

... signal processing, information theory, probability/statistics, estimation/detection, pattern recognition, optimization, image processing, and machine vision. Experience with machine learning ...

Vadum Inc

DSP Engineer

Raleigh, NC

$125K - $180K/yr

... signal processing, information theory, probability/statistics, estimation/detection, pattern recognition, optimization, image processing, and machine vision. Experience with machine learning ...

Vadum, Inc.

DSP Engineer

Raleigh, NC · On-site

$125K - $180K/yr

... signal processing, information theory, probability/statistics, estimation/detection, pattern recognition, optimization, image processing, and machine vision. Experience with machine learning ...

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All JobsSignal Processing Machine Learning JobsSignal Processing Machine Learning Jobs in North Carolina

Signal Processing Machine Learning information

See North Carolina salary details

$48.6K

$119.4K

$175.9K

How much do signal processing machine learning jobs pay per year?

As of Aug 15, 2026, the average yearly pay for signal processing machine learning in North Carolina is $119,370.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,600.00 and $134,000.00 per year, depending on experience, location, and employer.

What does a signal processing machine learning do?

As a Signal Processing Machine Learning professional, you can expect to work on projects that involve developing and optimizing algorithms for tasks such as audio or image recognition, anomaly detection, or sensor data analysis. Daily responsibilities often include pre-processing and cleaning large datasets, feature extraction, building and training machine learning models, and validating system performance. Collaboration with cross-functional teams—such as hardware engineers, data scientists, and software developers—is common to integrate your solutions into products or services. The work environment is typically dynamic and may involve both research-oriented tasks and practical implementation to create impactful, data-driven applications.

What is a signal processing machine learning?

A Signal Processing Machine Learning job involves developing algorithms that analyze and process signals (such as audio, images, video, or sensor data) using machine learning techniques. Professionals in this role apply concepts from digital signal processing (DSP) to extract meaningful patterns, enhance signal quality, and improve data-driven predictions. They work in diverse fields like telecommunications, biomedical engineering, finance, and autonomous systems. Typical tasks include feature extraction, noise reduction, and deploying deep learning models for real-time signal interpretation. Strong skills in mathematics, programming (Python, MATLAB), and frameworks like TensorFlow or PyTorch are essential.

What are the key skills and qualifications needed to thrive in signal processing machine learning?

To thrive in Signal Processing Machine Learning, you need a strong background in mathematics, digital signal processing, and machine learning, generally supported by a relevant degree in electrical engineering, computer science, or a related field. Experience with programming languages such as Python or MATLAB, familiarity with frameworks like TensorFlow or PyTorch, and knowledge of signal processing libraries are typically required. Analytical thinking, problem-solving ability, and effective communication are crucial soft skills in this position. These competencies enable you to design, implement, and refine advanced algorithms that address complex, real-world data challenges.

What are popular job titles related to Signal Processing Machine Learning jobs in North Carolina?

For Signal Processing Machine Learning jobs in North Carolina, the most frequently searched job titles are:

What job categories do people searching Signal Processing Machine Learning jobs in North Carolina look for?

The top searched job categories for Signal Processing Machine Learning jobs in North Carolina are:

Signal Processing Machine Learning jobs near you
Infographic showing various Signal Processing Machine Learning job openings in North Carolina as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $119,370 per year, or $57.4 per hour.

Machine Learning Engineer

Bespoke Labs

Greenville, NC • On-site

Full-time

Re-posted 29 days ago

Job description

About Us

We are AI researchers and builders who understand how to curate data and RL environments that truly improve models. We curated OpenThoughts, one of the best open reasoning datasets, and have trained SOTA models such as Bespoke-MiniCheck and Bespoke-MiniChart.

We are embarked on a journey to build Environments that are entire digital worlds that can be used to push the frontier of agents.

What You'll Be Working On

You will work directly with our research team on RL environment and task creation for agent training. This means designing observation spaces, action spaces, reward signals, and success criteria for new environments — and building the infrastructure that makes world-scale RL training possible. This is a high-ownership role; you will be building novel systems, not maintaining legacy ones.

Must-Have Skills

3+ years of ML engineering experience — model training, fine-tuning, or post-training pipelines in research or production

Strong Python and deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed precision)

Hands-on experience with LLM post-training — SFT, RLHF, PPO, DPO, or reward model training — and understanding of how training data quality affects model behavior

Familiarity with RL frameworks (Gymnasium, dm_env) and the ability to design or modify reward functions for agent training objectives

Experience running experiments at scale on cloud or HPC (AWS, GCP, SLURM, or Ray)

Solid understanding of evaluation methodology — held-out sets, benchmark design, avoiding train/eval contamination

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