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Apple Machine Learning Engineer Jobs in Atlanta, GA

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$220K - $280K/yr

As a Staff Machine Learning Engineer, you will lead the technical charge to scale and productionize our core machine learning capabilities. Your work will directly impact key metrics like Time-to-Bet ...

Machine Learning Engineer

Duluth, GA · On-site

$120 - $180/hr

Productionalizemodels-- packagemodelsfordeploymentonAzureML/Fabric,withMLflow-basedregistry,monitoring,andretrainingpipelines Skills/Requirements * 4-8 years of data science and/or ML engineering ...

Senior Machine Learning Engineer

Atlanta, GA · On-site

$100K - $138K/yr

As a 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 be asked to provide our business with insight and ...

Senior Machine Learning Engineer

Atlanta, GA · On-site

$100K - $138K/yr

As a 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 be asked to provide our business with insight and ...

Senior Machine Learning Engineer

Atlanta, GA · On-site

$100K - $138K/yr

As a 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 be asked to provide our business with insight and ...

Job Overview The Data Scientist / ML Engineer builds and deploys predictive models and analytical ... Machine learning breadth - classification, regression, clustering, recommendation systems; can ...

Machine Learning Engineer

Atlanta, GA · On-site

$85.92 - $130/hr

* Senior MLOps Engineer (Contractor) About the Role: * Client is seeking an experienced Senior MLOps Engineer to join client's Data Science Enablement (MLOps) team as a contractor. * Candidates will be ...

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ...

Sr Machine Learning Engineer

Atlanta, GA · On-site

$159K - $276K/yr

... Machine Learning driven features with Python (including NumPy, SciPy, Pandas, TensorFlow, Pytorch) Other Qualifications: * Strong programming skills in Python with proficiency in relevant libraries ...

Showing results 21-40

Apple Machine Learning Engineer information

See Atlanta, GA salary details

$30.3K

$123.8K

$186.1K

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

As of Aug 11, 2026, the average yearly pay for apple machine learning engineer in Atlanta, GA is $123,832.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,600.00 and $149,100.00 per year, depending on experience, location, and employer.

Is machine learning a high paying job?

Machine learning engineers typically earn high salaries due to the specialized skills required, such as proficiency in programming, data analysis, and model development. Salaries vary based on experience, location, and industry, but overall, it is considered a well-compensated field within technology roles.

What collaboration opportunities can an Apple machine learning engineer expect when working on cross-functional projects?

As an Apple Machine Learning Engineer, you will frequently collaborate with cross-functional teams including software engineers, product managers, and user experience designers. This collaboration is essential for integrating machine learning solutions seamlessly into Apple’s products and services. You can expect to participate in regular meetings to align on project goals, share technical insights, and troubleshoot challenges together. Such teamwork not only enhances product quality but also offers valuable opportunities for professional growth and skill development within Apple’s innovative environment.

What does an Apple machine learning engineer do?

An Apple Machine Learning Engineer designs, develops, and implements machine learning models and algorithms that power Apple's products and services. They work with large datasets, collaborate with software and hardware teams, and contribute to features such as Siri, image recognition, and personalized recommendations. Their role involves researching new techniques, optimizing models for performance and efficiency, and ensuring privacy and security standards are maintained.

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

AspectApple Machine Learning EngineerApple Data Scientist
Required CredentialsBachelor's or Master's in CS, ML, or related fields; experience with ML frameworksBachelor's or Master's in CS, Statistics, or related fields; strong analytical skills
Work EnvironmentDeveloping ML models, algorithms, deploying on Apple devicesAnalyzing data, building insights, supporting product decisions
Employer & Industry UsageTech industry, Apple-specific projects, hardware/software integrationTech industry, product analytics, user behavior insights

Apple Machine Learning Engineers focus on developing and deploying ML models within Apple's ecosystem, while Apple Data Scientists analyze data to inform product decisions. Both roles require strong technical skills, but ML Engineers are more involved in model creation and deployment, whereas Data Scientists focus on data analysis and insights.

What are the key skills and qualifications needed to thrive as an Apple machine learning engineer, and why are they important?

To thrive as an Apple Machine Learning Engineer, you need a strong background in computer science, mathematics, and statistics, typically with experience in machine learning algorithms and a relevant degree. Expertise in programming languages such as Python or Swift, familiarity with frameworks like TensorFlow or PyTorch, and knowledge of Apple's Core ML are commonly required. Strong problem-solving abilities, creativity, and effective communication help you collaborate across teams and translate complex ideas. These skills ensure innovative, scalable, and user-centric machine learning solutions that align with Apple's high standards.

How do I get into Apple as an Apple Machine Learning Engineer?

To become an Apple Machine Learning Engineer, candidates typically need a strong background in computer science, machine learning, or related fields, with proficiency in programming languages like Python and experience with frameworks such as TensorFlow or PyTorch. Relevant skills include data analysis, model development, and familiarity with Apple's ecosystem, often supported by a bachelor's or master's degree and a strong portfolio of projects or research. Applying through Apple's careers website and demonstrating technical expertise during interviews are essential steps.
What are the most commonly searched types of Apple Machine Learning Engineer jobs in Atlanta, GA? The most popular types of Apple Machine Learning Engineer jobs in Atlanta, GA are:
Infographic showing various Apple Machine Learning Engineer job openings in Atlanta, GA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 21% Part Time, 1% Temporary, and 4% Contract. Highlights an 85% Physical, 2% Hybrid, and 13% Remote job distribution, with an average salary of $123,832 per year, or $59.5 per hour.

Staff Machine Learning Engineer

PrizePicks

Atlanta, GA • On-site, Remote

$220K - $280K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 6 days ago


Job description

At PrizePicks, we are the fastest-growing sports company in North America, as recognized by Inc. 5000. As the leading platform for Daily Fantasy Sports, we cover a diverse range of sports leagues, including the NFL, NBA, and Esports titles like League of Legends and Counter-Strike. Our team of over 550 employees thrives in an inclusive culture that values individuals from diverse backgrounds, regardless of their level of sports fandom. Ready to reimagine the DFS industry together?
As a Staff Machine Learning Engineer, you will lead the technical charge to scale and productionize our core machine learning capabilities. Your work will directly impact key metrics like Time-to-Bet, Deposit Velocity, and Platform Integrity by integrating robust, low-latency ML models across our sports betting and daily fantasy ecosystems.
What you'll do:
  • Architect Scalable ML Systems: Design and build the end-to-end machine learning infrastructure, transitioning experimental Data Science models into robust, high-availability production services.
  • Real-Time Inference at Scale: Steer the design and deployment of low-latency services to serve model inferences in milliseconds. You will power real-time decisions across the platform, from dynamic oddsmaking and risk analysis to smart deposit defaults.
  • Feature Engineering & Data Strategy: Partner with Data Science to build scalable logging and data pipelines. You will lead the creation and optimization of a centralized feature store required to train complex models across diverse business domains.
  • End-to-End MLOps Leadership: Champion best practices for model deployment, monitoring, and CI/CD for ML. You will implement automated retraining pipelines and observability tools to ensure data drift and model degradation are caught and addressed instantly.
What you have:
  • 7+ years of experience in Machine Learning Engineering or Backend Engineering, with a proven track record of deploying and maintaining complex ML models in high-traffic production environments.
  • 3+ years of technical leadership, acting as a lead and driving architecture decisions for consumer applications or scalable backend platforms.
  • Experience with Real-Time Data: Proficient in streaming architectures (Kafka/Flink/PubSub) and building low-latency services to serve model inference in <100ms.
  • MLOps Expertise: Deep experience managing the full ML lifecycle (training, deploying, monitoring) using tools like MLFlow, Kubeflow, Databricks, or SageMaker.
  • Strong Coding Skills: Expert in Python and SQL; proficiency in Go, C++, or Rust is a strong plus for building high-performance inference layers.
  • Cloud Native: Deep experience with GCP services (BigQuery, Cloud Functions, GKE, Vertex AI) or AWS equivalents.
What makes you stand out:
  • Experience implementing reinforcement learning or complex probabilistic models for dynamic pricing, risk management, or fraud detection.
  • Background in Daily Fantasy Sports (DFS), oddsmaking, or high-frequency trading.
  • Experience building and scaling "Feature Stores" that successfully bridge batch historical data with real-time event streams.
Where you'll live:
  • While we prefer candidates based in Atlanta, we are open to qualified applicants from anywhere in the U.S. and are willing to consider remote candidates. #LI-Remote
Working at PrizePicks:
The typical salary range for this position is $220,000 to $280,000. At PrizePicks, we consider your role, level, and where you'll be working when determining our salary ranges. The compensation info you see on our job postings gives you an idea of the starting pay range for the position. Your actual pay within that range will depend on your specific work location, as well as your skills, experience, and education. Your recruiter will be happy to chat more about the specific pay range for your location and how we arrived at it during the hiring process.
This application period will remain open for 30 days. We're committed to finding the best candidate, so this date may be adjusted, and any changes will be reflected in this posting.
Date Posted: 4/16/2026
1st Extension: 5/16/2026
2nd Extension: 6/16/2026
Benefits you'll receive:
In addition to your great compensation package, full-time employees will be eligible for the following perks:
  • Company-subsidized medical, dental, & vision plans
  • 401(k) plan with company match
  • Annual bonus
  • Flexible PTO to encourage a healthy work/life balance (2 weeks STRONGLY encouraged!)
  • Generous paid leave programs, including 16-week paid parental leave and disability benefits
  • Workplace flexibility and modern work schedules focused on getting the job done, not hours clocked
  • Company-wide in-person events and team outings
  • Lifestyle enhancement program
  • Company equipment provided (Windows & Mac options)
  • Annual performance reviews with opportunities for growth and career development

You must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.
PrizePicks is an Equal Opportunity Employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.