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Machine Learning Engineer Opt Jobs in Conyers, GA

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 ... No OPT, CPT, STEM/OPT or visa sponsorship now or in future. * Bachelor's degree in a related ...

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 ... No OPT, CPT, STEM/OPT or visa sponsorship now or in future. * Bachelor's degree in a related ...

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 ... No OPT, CPT, STEM/OPT or visa sponsorship now or in future. * Bachelor's degree in a related ...

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 ... No OPT, CPT, STEM/OPT or visa sponsorship now or in future. * Bachelor's degree in a related ...

Machine Learning Lead Engineer

Atlanta, GA · On-site

$134K - $224K/yr

We are seeking a visionary Machine Learning Engineer Lead to spearhead our experimental ML ... No OPT, CPT, STEM/OPT or visa sponsorship now or in future. * Bachelor's degree in a related ...

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 ... No OPT, CPT, STEM/OPT or visa sponsorship now or in future. * Bachelor's degree in a related ...

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Showing results 1-20

Machine Learning Engineer Opt information

See Conyers, GA salary details

$27.6K

$112.7K

$169.4K

How much do machine learning engineer opt jobs pay per year?

As of Jul 13, 2026, the average yearly pay for machine learning engineer opt 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 are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

What is the difference between Machine Learning Engineer Opt vs Data Scientist?

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

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 a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

What are some common challenges Machine Learning Engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.
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Machine Learning Engineer

Other

Posted 2 days ago


Job description

Job Description Machine Learning Engineer Roles and Responsibilities Lead the end-to-end architecture and development of machine learning solutions. Implement machine learning algorithms into services and pipelines to be consumed at large-scale. Engineer large scale development systems using full-stack, distributed shallow and deep-learning technologies and big data technologies.

Architect and develop a highly scalable, distributed, multi-tenant set of microservices backend solutions. Be a part of a highly productive and creative engineering team What Are We Looking For in This Role. Highly Preferred: MS or PhD in Machine learning, Computer Vision, Natural Language Processing or a related field.

5+ years of experience architecting and developing AI and machine learning applications Ability to think critically, question assumptions and devise solutions to challenging technical problems. Hands-on experience with one or more of the following technologies: --Machine Learning: TensorFlow, PyTorch, Spark ML/MLib etc. --ML Technologies: NLP, Computer Vision and related technologies.

--Back end web-services: Java, Spring Boot, Python, Kubernetes, Docker - Big Data technologies: Kafka, Apache Spark, MapR, Hbase, Hive, HDFS etc. Minimum Qualifications Bachelor's Degree Relevant Experience or Degree in: Computer Science, Management Information Systems, Business or related field Typically Minimum 6 Years Relevant Exp Four-year college degree and 6 or more years, and/or a high school diploma with 8 or more years professional experience with full life cycle design and development