1

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

Knowledge of statistics, data science, AI/machine learning, big data management * Strong ... Familiarity with DevOps, CI/CD (Github Actions, etc), bash, UNIX/Linux commands, etc * Familiar ...

The MLOps Engineer works closely with Machine Learning Engineers and Data Engineers to ensure that models and decisioning systems are production-ready, observable, cost-efficient, and seamlessly ...

As a Staff Machine Learning Engineer at FanDuel, you will help us unlock the full potential of our vast amounts of real-time and relational data. You will own critical production ML systems across ...

Senior Machine Learning Engineer (MLOPS)

Atlanta, GA ยท On-site

$100K - $138K/yr

Collaborate with data engineering teams to ensure clean, reliable data pipelines (such as Medallion architectures) seamlessly feed into machine learning models. * Engineering Best Practices: Write ...

Lead Machine Learning Engineer - REMOTE

Atlanta, GA ยท Remote

$98K - $129K/yr

Join a Company that Empowers you to Build your Future Lennar is seeking a Machine Learning Engineer to own and evolve the infrastructure and surface mechanisms that take our data science and ML ...

About the role As a Staff AI Engineer at Tonic, you'll own the models that make Tonic's data trustworthy - training the synthesis models that replace sensitive data with something realistic enough to ...

Showing results 41-60

Machine Learning Engineer information

See Duluth, GA salary details

$29K

$118.5K

$178.1K

How much do machine learning engineer jobs pay per year?

As of Aug 21, 2026, the average yearly pay for machine learning engineer in Duluth, GA is $118,522.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,400.00 and $142,700.00 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.

What are the most commonly searched types of Machine Learning Engineer jobs in Duluth, GA?

The most popular types of Machine Learning Engineer jobs in Duluth, GA are:

What are popular job titles related to Machine Learning Engineer jobs in Duluth, GA?

For Machine Learning Engineer jobs in Duluth, GA, the most frequently searched job titles are:

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

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

Infographic showing various Machine Learning Engineer job openings in Duluth, GA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 24% Part Time, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $118,522 per year, or $57 per hour.

Staff Machine Learning Engineer

Dolby

Atlanta, GA โ€ข On-site

Full-time

Re-posted 5 days ago


Job description

Join the leader in entertainment innovation and help us design the future. At Dolby, science meets art, and high tech means more than computer code. As a member of the Dolby team, you'll see and hear the results of your work everywhere, from movie theaters to smartphones. We continue to revolutionize how people create, deliver, and enjoy entertainment worldwide. To do that, we need the absolute best talent. We're big enough to give you all the resources you need, and small enough so you can make a real difference and earn recognition for your work. We offer a collegial culture, challenging projects, and excellent compensation and benefits, not to mention a Flex Work approach that is truly flexible to support where, when, and how you do your best work.
The Advanced Technology Group (ATG) is the research division of the company. ATG's mission is to look ahead, deliver insights, and innovate technological solutions that will fuel Dolby's continued growth. Our researchers have a broad range of expertise related to computer science and electrical engineering, such as AI/ML, algorithms, digital signal processing, audio engineering, image processing, computer vision, data science & analytics, distributed systems, cloud, edge & mobile computing, computer networking, and IoT.
Sight and Sound play a large role in our day-to-day experiences. We believe data can play a huge role in making the experiences personalized and resilient. Data is critical to synthesizing experiences that are otherwise unimaginable.
We're looking for a talented Staff Data/ML Engineer who is excited to advance the state of the art in technologies of interest to Dolby as well as the human society at large. Research in the areas of data platforms, distributed processing systems, and data science at Dolby Laboratories focuses on all aspects of large-scale cloud and data processing platforms and services, and novel ways to accelerate discovering insight from data. We are interested in a variety of topics including large-scale distributed systems, stream processing, edge computing, applied machine learning and AI, big graphs, natural language processing, big data management, and heterogenous data analytics.
Specifically, we are looking for an architect who is passionate about combining science with art-translating research into AI-enabled, low latency real-time streaming systems and applications, which enable the next generation of immersive experiences.
You will:
Partner with Dolby researchers, understand the AI based Imaging/Audio algorithms and optimize the algorithm to run in Cloud and end device in a distributed way.
Be a key part of a team which is trying to figure out how to do low latency cloud offloading of complex algorithm. T
Partner to develop a Cloud backend solution, Web App and mobile applications for Android/iOS which connect to the Cloud backend.
Key Responsibilities:
  • Design and implement advanced data platforms, unified data models spanning structured and unstructured data sets, and data-enabling systems like metadata management services to support training and inference of AI/ML models in hybrid-cloud environment.
  • Design and implement cloud-based, distributed software architectures and microservice-based platforms to enable low latency, real-time streaming and complex event processing that deliver Dolby's next gen Audio/Visual experiences in the cloud or on end-user devices.
  • Develop new applications, novel data collection tools, and instrumentation regimes that enable an amazing variety of interactive and immersive data-driven experiences by inferring context of both content and the world around us using AI-based techniques.
  • Consult and implement data governance and management policies to support Dolby's position as trusted custodian in the media, entertainment, and technology ecosystems.
  • Partner with ATG researchers to understand data and advanced cloud system-related opportunities in adjacent research domains such as applied AI and machine learning in Audio / Video domains.

What you need to succeed
Competencies
  • Technical depth: Necessary technical knowledge to create new SW architecture, platforms, and enabling systems needed for real-time, just-in-time processing for audio/video algorithms running on distributed fashion between cloud and edge devices. Basic knowledge on Audio/Video streaming formats.
  • Explore new technologies: Openness to learn new areas and innovate in the new areas.
  • Invent & Innovate: Develop short and long-term technologies, algorithms and software tools that will help make Dolby a world leader in enhancing the sight and sound associated with digital content consumption. Then influence and collaborate with BG partners put the technology into production.
  • Work with a sense of Urgency: Responds aggressively to changing trends and new technologies and creates new algorithms to capitalize on them. Takes appropriate risks to be ahead of the competition and the market.
  • Collaborate: Collaborate with and influence peers in developing industry-leading technologies. Work with external trendsetters and technology drivers in academia and in partner enterprises.

Desired Background
  • Masters in Computer Science or related field, PHD is a plus
  • 5+ years of professional experience with relevant experience building and designing distributed data systems
  • Knowledge of statistics, data science, AI/machine learning, big data management
  • Strong proficiency in Python and an additional language (e.g., C++, Golang, Rust, etc)
  • Expertise in data structures, distributed algorithms (consensus, coordination, etc), data modeling, and data analytic techniques of heterogenous, stream-based data
  • 4+ years of experience in cloud systems, distributed computing architectures (n-tier, peer-to-peer, microservices), service design and implementation (REST, Thrift/gRPC, etc), container orchestration (Kubernetes) and optimization techniques
  • Experience with real-time messaging and streaming architectures, platforms, and frameworks (PubSub/Kafka, Storm, Kinesis, Dataflow/Beam, Flink, Spark Streaming, etc)
  • Experience with AI/ML models, cloud-optimization, and software development patterns
  • Familiarity with DevOps, CI/CD (Github Actions, etc), bash, UNIX/Linux commands, etc
  • Familiar with git and project management tools, such as JIRA
  • Excellent problem-solving and partnership skills
  • Excellent communication and presentation skills
  • Desired: Knowledge of Audio/Video formats, processing, editing, and streaming.
  • Bonus: Experience with deep learning frameworks, e.g., TensorFlow, PyTorch, etc., is a plus.
  • Bonus: Experience with Databricks / Spark

The Atlanta Area base salary range for this full-time position is $180,800 -$209,200, which can vary if outside this location,plus bonus, benefits, and some roles may also include equity. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, competencies, experience, market demands, internal parity, and relevant education or training. Your recruiter can share more about the specific salary range and perks and benefits for your location during the hiring process.
Dolby will consider qualified applicants with criminal histories in a manner consistent with the requirements of San Francisco Police Code, Article 49, and Administrative Code, Article 12
Equal Employment Opportunity:
Dolby is proud to be an equal opportunity employer. Our success depends on the combined skills and talents of all our employees. We are committed to making employment decisions without regard to race, religious creed, color, age, sex, sexual orientation, gender identity, national origin, religion, marital status, family status, medical condition, disability, military service, pregnancy, childbirth and related medical conditions or any other classification protected by federal, state, and local laws and ordinances.