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Audio Machine Learning Jobs in Georgia (NOW HIRING)

Cox Automotive

Machine Learning Lead Engineer

Redan, GA · On-site

$134K - $224K/yr

We are seeking a visionary Machine Learning Engineer Lead to spearhead our experimental ML ... audio) to uncover patterns and develop practical solutions. Possesses deep knowledge in at least ...

Cox Automotive

Machine Learning Lead Engineer

Decatur, GA · On-site

$134K - $224K/yr

We are seeking a visionary Machine Learning Engineer Lead to spearhead our experimental ML ... audio) to uncover patterns and develop practical solutions. Possesses deep knowledge in at least ...

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Audio Machine Learning information

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$24.9K

$71.3K

$144.8K

How much do audio machine learning jobs pay per year?

As of Jun 23, 2026, the average yearly pay for audio machine learning in Georgia is $71,313.00, according to ZipRecruiter salary data. Most workers in this role earn between $42,200.00 and $95,400.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Audio Machine Learning position, and why are they important?

To thrive in Audio Machine Learning, you need a strong background in machine learning, digital signal processing, and proficiency with programming languages such as Python or MATLAB, typically supported by a relevant degree in computer science, electrical engineering, or a related field. Familiarity with frameworks like TensorFlow or PyTorch, experience with audio libraries (e.g., Librosa), and knowledge of cloud computing tools are highly valued, as are certifications in AI or data science. Strong problem-solving skills, creativity, and effective communication are essential soft skills for success in this field. These skills are crucial for developing innovative solutions, collaborating across multidisciplinary teams, and addressing complex audio data challenges in real-world projects.

What are the typical daily responsibilities of someone working in Audio Machine Learning?

Professionals in Audio Machine Learning typically spend their days designing, developing, and optimizing machine learning models tailored to audio data, such as speech or music recognition systems. You may also preprocess large datasets, extract and engineer relevant features, and collaborate closely with data scientists, audio engineers, and software developers to integrate your work into larger applications. Regular tasks often include running experiments, evaluating model performance, tuning hyperparameters, and keeping up with the latest advancements in the field. Team meetings, code reviews, and presenting findings to stakeholders are also common parts of the workweek.

What is an Audio Machine Learning job?

An Audio Machine Learning job involves developing algorithms and models that analyze, process, and generate audio data. Responsibilities typically include working with speech recognition, music analysis, sound classification, and audio enhancement. Professionals in this field use deep learning, signal processing, and neural networks to improve audio-based applications like voice assistants, noise reduction systems, and music recommendation engines. They often work with datasets of speech, music, or environmental sounds to build models that understand and manipulate audio signals effectively.

What is the salary of audio AI engineer?

The salary of an audio AI engineer typically ranges from $80,000 to $150,000 annually, depending on experience, location, and company size. Professionals with expertise in machine learning, signal processing, and programming languages like Python or TensorFlow tend to earn higher salaries.

What is a $900,000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as senior machine learning engineer or AI research director, often requiring advanced skills in deep learning, data science, and programming. These roles usually involve leadership, extensive experience, and may include stock options or bonuses, especially in large tech companies or startups. Compensation at this level reflects significant expertise and responsibility in developing and deploying AI systems.

Which 5 jobs will survive AI?

Audio Machine Learning professionals are likely to continue in roles that require creative interpretation, complex problem-solving, and domain expertise, such as audio engineers, sound designers, data scientists, AI specialists, and research scientists. These roles involve tasks that are difficult to fully automate, especially those requiring nuanced understanding of sound and human perception. Skills in programming, signal processing, and domain-specific knowledge will remain valuable in these jobs.

What engineers make $500,000?

Senior audio machine learning engineers with extensive experience, advanced skills in deep learning, and proficiency in tools like Python and TensorFlow can reach salaries of $500,000 or more, especially in high-cost-of-living areas or at leading tech companies. Achieving this level often requires a strong track record, specialized knowledge in audio processing, and sometimes equity or bonuses as part of compensation packages.
What are the most commonly searched types of Audio Machine Learning jobs in Georgia? The most popular types of Audio Machine Learning jobs in Georgia are:
What are popular job titles related to Audio Machine Learning jobs in Georgia? For Audio Machine Learning jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Audio Machine Learning jobs in Georgia look for? The top searched job categories for Audio Machine Learning jobs in Georgia are:
Audio Machine Learning jobs near you
Machine Learning Lead Engineer

Machine Learning Lead Engineer

Cox Automotive

Doraville, GA

$134K - $224K/yr

Full-time

PTO

Posted 18 days ago

Cox Automotive rating

7.8

Company rating: 7.8 out of 10

Based on 135 frontline employees who took The Breakroom Quiz

88th of 138 rated financial services

Job description

We are seeking a visionary Machine Learning Engineer Lead to spearhead our experimental ML initiatives and drive innovation across the organization. This role combines technical leadership in cutting-edge research with the responsibility of building a culture of continuous learning and knowledge sharing. You'll lead efforts to identify, evaluate, and prototype emerging ML technologies while establishing our company as a thought leader in the ML community. Applies AI and Machine Learning (AI/ML) principles to design, test, and scale frameworks, systems, and models for big data predictive applications. Develops AI/ML-powered solutions based on business needs. Researches, implements, and tests machine learning methods to create product features, automate workflows, extract insights from data, and improve data quality. Structures, trains, and deploys models to learn from complex data across multiple modalities (e.g., structured, unstructured, image, video, audio) to uncover patterns and develop practical solutions. Possesses deep knowledge in at least one sub-area of machine learning, such as deep learning, generative AI, computer vision, optimization, predictive models, or causal machine learning.
WHAT YOU'LL DO
Key Responsibilities
  • Accelerate ML development using AI tools for code generation, feature engineering, optimization, and validation
  • Stay up to date with advancements in ML, AI, and emerging technologies
  • Design, build, and maintain ML models, algorithms, and robust pipelines for data processing, training, and inference
  • Optimize model performance, scalability, and reliability in production environments
  • Collaborate cross-functionally to translate model insights into business value and communicate project updates
  • Contribute to ML infrastructure improvements, best practices, and documentation
  • Partner with engineering teams to integrate AI-enhanced models and establish automated monitoring frameworks.
  • Establish AI governance practices including bias detection, interpretability, compliance monitoring, and responsible deployment.
  • Mentor teams in AI adoption, share best practices, and promote responsible AI innovation culture.
  • Lead AI transformation initiatives including tool evaluation, governance development, and strategic adoption planning.
  • Analyzes complex data sets to solve real-world business and customer use cases.
  • Performs end-to-end development of machine learning models
  • May assist with or lead the development of industry whitepapers or other technical publications.
  • Continuously evaluate AI processes for accuracy, efficiency, and business impact while staying current on emerging technologies.
  • Design agentic workflows for autonomous training, data pipelines, and analytical problem solving appropriate to experience level.

Key AI Use Cases
  • AI-Accelerated Model Development: Use GitHub Copilot, Claude Code for rapid ML prototyping, automated feature engineering, and intelligent hyperparameter optimization.
  • Agentic ML Workflows: Understand and deploy (P4+) AWS AgentSquad, AWS Strands, LangChain agents for autonomous training pipelines, multi-step analysis, and collaborative research.
  • AI-Enhanced Model Interpretation: Build on traditional frameworks (SHAP, LIME) with AI tools for enhanced stakeholder communication and automated insights.
  • AI-Powered Research: Leverage manual/autonomous competitive intelligence and research acceleration tools for methodology discovery and algorithm innovation.

WHO YOU ARE
Required Skills
  • Proficiency in AI development tools (GitHub Copilot, Claude, GPT-4) for ML development with ability to validate AI outputs for production readiness.
  • Understanding of agentic frameworks (AWS AgentSquad, AWS Strands, LangChain, agent patterns) with progression from basic configuration to custom enterprise system design.
  • Knowledge of AI ethics, responsible AI practices, and governance frameworks for business-critical ML deployment.
  • Ability to leverage AI like Co-Pilot for technical communication to stakeholders and cross-functional collaboration.
  • Commitment to continuous learning in AI-augmented data science and responsible AI use.

Required Qualifications
  • Applicants must currently be authorized to work in the United States for any employer without current or future sponsorship. No OPT, CPT, STEM/OPT or visa sponsorship now or in future.
  • Bachelor's degree in a related discipline and 6 years' experience in Machine Learning; or a different combination, such as a master's degree and 4 years' experience; a Ph.D. and 1 years' experience in a related field; or 18 years' experience in a related field with no degree
  • Minimum of 6 years of experience as a Machine Learning Engineer or equivalent
  • Deep expertise in multiple ML domains and familiarity with emerging research areas
  • Strong experience in technology evaluation, competitive analysis, and strategic planning
  • Comfortability with non-deterministic systems
  • Product background- understand how to prioritize, collaborate across teams, manage dependencies with others, set strategy
  • Experience in Rally, Jira or similar tools
  • Skilled in analytical thinking, consulting, requirements analysis, system and technology integration and technology savvy.
  • Skilled in collaborating with intent, communicating with impact, developing trust, driving innovation and striving for excellence.
  • Proven track record of leading innovative projects from concept to proof-of-concept
  • Demonstrated success in knowledge sharing and thought leadership (publications, speaking, etc.)
  • Experience building and leading high-performing research or innovation teams
  • Excellent communication skills for technical and executive audiences
  • Strong network within the ML research community
  • Experience with research collaboration and partnership development
  • Other duties as needed or required
  • Must be comfortable with change and an evolving environment

Preferred Qualifications
  • Experience in corporate research labs, innovation teams, or technology consulting
  • Track record of identifying and successfully implementing breakthrough technologies
  • Background in technology transfer from research to business applications
  • Strong presence in the ML community (conference speaking, open-source contributions, etc.)
  • Knowledge of emerging areas such as LLMs, Agents, foundation models, multimodal AI, or quantum ML

Leadership Expectations
  • Foster a culture of experimentation, learning, and calculated risk-taking
  • Drive consensus on research priorities while maintaining innovation velocity
  • Develop talent through mentoring in both technical skills and research methodologies
  • Communicate complex experimental results and strategic implications to all organizational levels
  • Lead by example in intellectual curiosity, scientific rigor, and knowledge sharing
  • Build bridges between cutting-edge research and practical business applications
  • Establish the team as a recognized center of excellence in experimental ML

USD 134,900.00 - 224,900.00 per year
Compensation:
Compensation includes a base salary in the range of $134,900.00 - $224,900.00. The base salary may vary within the anticipated base pay range based on factors such as the ultimate location of the position and the selected candidate's knowledge, skills, and abilities. Position may be eligible for additional compensation that may include an incentive program.
Benefits:
The Company offers eligible employees the flexibility to take as much vacation with pay as they deem consistent with their duties, the company's needs, and its obligations; seven paid holidays throughout the calendar year; and up to 160 hours of paid wellness annually for their own wellness or that of family members. Employees are also eligible for additional paid time off in the form of bereavement leave, time off to vote, jury duty leave, volunteer time off, military leave, and parental leave.
EOE, including disability/vets

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About Cox Automotive

Sourced by ZipRecruiter

At Cox Automotive, people of every background are driven by their passion for mobility, innovation and community. We transform the way the world buys, sells, owns and uses cars, accelerating the industry with global powerhouse brands like Autotrader, Kelley Blue Book, Manheim and more. What's more, we do it all with an emphasis on employee growth and happiness. Drive your future forward and join Cox Automotive today! Cox empowers employees to build a better future and has been doing so for over 120 years. With exciting investments and innovations across transportation, communications, cleantech and healthcare, our family of businesses - which includes Cox Automotive and Cox Communications - is forging a better future for us all. Ready to make your mark? Join us today! Benefits of working at Cox may include health care insurance (medical, dental, vision), retirement planning (401(k)), and paid days off (sick leave, parental leave, flexible vacation/wellness days, and/or PTO). For more details on what benefits you may be offered, visit our benefits page . Cox is an Equal Employment Opportunity employer - All qualified applicants/employees will receive consideration for employment without regard to that individual's age, race, color, religion or creed, national origin or ancestry, sex (including pregnancy), sexual orientation, gender, gender identity, physical or mental disability, veteran status, genetic information, ethnicity, citizenship, or any other characteristic protected by law. Cox provides reasonable accommodations when requested by a qualified applicant or employee with disability, unless such accommodations would cause an undue hardship. Statement to ALL Third-Party Agencies and Similar Organizations: Cox accepts resumes only from agencies with which we formally engage their services. Please do not forward resumes to our applicant tracking system, Cox employees, Cox hiring manager, or send to any Cox facility. Cox is not responsible for any fees or charges associated with unsolicited resumes.

Industry

Automobile dealers and technology, communication and media

Company size

5,001 - 10,000 Employees

Headquarters location

Atlanta, GA, US

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