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Machine Learning Engineer Jobs in Conyers, GA (NOW HIRING)

Bespoke Labs

Machine Learning Engineer

Atlanta, GA

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

Cox Automotive

Machine Learning Lead Engineer

Pine Lake, GA · On-site

$134K - $224K/yr

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 ...

Cox Automotive

Machine Learning Lead Engineer

Chamblee, GA · On-site

$134K - $224K/yr

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 ...

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 initiatives and drive innovation across the organization. This role combines technical leadership in cutting ...

Cox Automotive

Machine Learning Lead Engineer

Norcross, GA · On-site

$134K - $224K/yr

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 ...

Cox Automotive

Machine Learning Lead Engineer

Hapeville, GA · On-site

$134K - $224K/yr

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 ...

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 initiatives and drive innovation across the organization. This role combines technical leadership in cutting ...

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 initiatives and drive innovation across the organization. This role combines technical leadership in cutting ...

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 initiatives and drive innovation across the organization. This role combines technical leadership in cutting ...

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Showing results 21-40

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Conyers, GA

Machine Learning Engineer information

See Conyers, GA salary details

$27.6K

$112.7K

$169.4K

How much do machine learning engineer jobs pay per year?

As of Sep 5, 2026, the average yearly pay for machine learning engineer in Conyers, GA is $112,729.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,900.00 and $135,700.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

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 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 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.

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.

More about Machine Learning Engineer jobs

What job categories do people searching Machine Learning Engineer jobs in Conyers, GA look for?

The top searched job categories for Machine Learning Engineer jobs in Conyers, GA are:

What cities near Conyers, GA are hiring for Machine Learning Engineer jobs?

Cities near Conyers, GA with the most Machine Learning Engineer job openings:

Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Conyers, GA as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $112,729 per year, or $54.2 per hour.

Machine Learning Engineer 3 (AI Engineer)

4pconsultinginc

Atlanta, GA • On-site

Contractor

Re-posted 20 days ago

Job description

Machine Learning Engineer 3 (AI Engineer)

Location: Atlanta, GA

Client- Southern Company Gas

Contract- 1 Year
 

Job Summary

We are seeking a highly skilled Machine Learning Engineer (Level 3) with 5–10 years of experience to design, develop, and deploy advanced AI models and systems. This role requires expertise in machine learning, data analysis, and model deployment to optimize business operations and drive innovation within the utilities and energy sector.

The successful candidate will collaborate with cross-functional teams—including data scientists, engineers, and business stakeholders—to integrate AI solutions into real-world applications that support operational efficiency, customer service, and sustainability initiatives.

Key Responsibilities

  • AI Model Development: Design and implement machine learning models and algorithms to address utility-specific challenges such as grid optimization, asset reliability, predictive maintenance, and customer analytics.

  • Data Analysis: Analyze large, complex datasets from SCADA, AMI, and IoT systems to extract actionable insights.

  • Model Training & Evaluation: Train, test, and validate AI models to ensure accuracy, scalability, and compliance with industry reliability standards.

  • Deployment & Integration: Deploy AI solutions into production systems and integrate with enterprise platforms (e.g., Azure, Maximo, EMS/DMS systems).

  • Innovation: Stay current with the latest advancements in AI/ML and recommend solutions that can enhance grid resilience, safety, and efficiency.

  • Collaboration: Partner with engineering, IT, and business units to define requirements and deliver business-aligned AI solutions.

  • Performance Monitoring: Continuously monitor AI models and refine as needed to maintain performance and compliance.

  • Documentation & Knowledge Sharing: Create clear documentation of models, workflows, and processes for reuse and compliance.

Qualifications

Education:

  • Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field.

Experience:

  • 5–10 years of experience in AI, ML, or data science roles, with proven success in AI model development and deployment.

  • Industry experience in utilities, energy, or large-scale infrastructure data is preferred.

Technical Skills:

  • Proficiency in Python, R, or Java.

  • Experience with ML frameworks: TensorFlow, PyTorch, scikit-learn.

  • Strong grasp of data structures, algorithms, and applied statistics.

  • Familiarity with cloud platforms such as Azure ML and Azure Databricks (preferred), AWS or Google Cloud (a plus).

  • Experience with big data tools (e.g., Spark, Hadoop) is desirable.

  • Exposure to natural language processing (NLP) or computer vision a plus.

Soft Skills:

  • Strong analytical and problem-solving abilities.

  • Excellent communication skills for cross-functional collaboration.

  • Ability to work independently and manage multiple projects simultaneously.

  • Experience working in agile or iterative development environments.

Preferred Qualifications

  • Lighting up AI/ML use cases in the utility/energy sector (e.g., outage prediction, DERMS optimization, vegetation management analytics).

  • Certifications in AI/ML, data science, or cloud platforms (Azure, AWS, GCP).

  • Experience with MLOps pipelines and CI/CD integration for model deployment.