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Remote Embedded Machine Learning Jobs in Georgia

Staff Machine Learning Engineer

Atlanta, GA ยท On-site +1

$220K - $280K/yr

As a Staff Machine Learning Engineer, you will lead the technical charge to scale and productionize ... S. and are willing to consider remote candidates. #LI-Remote Working at PrizePicks: The typical ...

Staff Machine Learning Engineer

Atlanta, GA ยท On-site +1

$220K - $280K/yr

As a Staff Machine Learning Engineer, you will lead the technical charge to scale and productionize ... S. and are willing to consider remote candidates. #LI-Remote Working at PrizePicks: The typical ...

Senior Machine Learning Engineer

Atlanta, GA ยท Remote

$165K - $225K/yr

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 ...

AI & Machine Learning * Build and scale the organization's AI/ML capabilities, including ... Ensure the platform supports real-time analytics, self-service BI, embedded analytics for customer ...

Adidev is looking for an adept Machine Learning Engineer to take the helm in deploying advanced ... Support, even from afar, with our remote assistance. Regular salary reviews? You betcha! Ready to ...

Adidev is looking for an adept Machine Learning Engineer to take the helm in deploying advanced ... Support, even from afar, with our remote assistance. Regular salary reviews? You betcha! Ready to ...

United States (Remote) Interested applicants must reside in one of the following approved states ... Enable future machine learning use cases by ensuring curated datasets are ML-ready, including ...

Senior AI Engineer

Atlanta, GA ยท On-site +1

$100K - $138K/yr

We offer unlimited PTO, a flexible remote work policy, and a supportive environment that ... The Senior AI Engineer 1 (Senior Staff) leads the development of advanced AI and machine learning ...

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Remote Embedded Machine Learning information

What are the key skills and qualifications needed to thrive as a Remote Embedded Machine Learning Engineer, and why are they important?

To thrive as a Remote Embedded Machine Learning Engineer, you need a solid background in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often supported by a degree in computer science, electrical engineering, or related fields. Familiarity with microcontrollers, edge AI frameworks (such as TensorFlow Lite or Edge Impulse), and version control systems is typically required. Strong problem-solving skills, effective communication, and self-motivation are essential soft skills for collaborating remotely and troubleshooting complex issues. These skills ensure successful deployment of intelligent solutions on resource-constrained devices and effective teamwork in distributed environments.

What is a Remote Embedded Machine Learning Engineer?

A Remote Embedded Machine Learning Engineer is a professional who develops and deploys machine learning models on embedded systems like microcontrollers, IoT devices, and edge hardware, all while working remotely. Their work involves optimizing algorithms to run efficiently on devices with limited computing power, memory, and battery life. These engineers typically use frameworks such as TensorFlow Lite or TinyML to design intelligent features that operate directly on hardware, enabling real-time decision-making without relying heavily on cloud connectivity. They collaborate with cross-functional teams and often troubleshoot both software and hardware issues from a remote location.

What is the difference between Remote Embedded Machine Learning vs Remote Data Scientist?

AspectRemote Embedded Machine LearningRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Electrical Engineering, or related fields; experience with embedded systems and ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in data analysis and ML algorithms
Work EnvironmentEmbedded hardware devices, IoT systems, real-time processing environmentsCloud platforms, data analysis labs, remote offices
Employer & Industry UsageTech companies, IoT device manufacturers, automotive, roboticsFinance, healthcare, marketing, tech firms

Remote Embedded Machine Learning specialists focus on integrating ML models into embedded hardware for real-time applications, often working with IoT and robotics. In contrast, Remote Data Scientists analyze large datasets to extract insights, primarily working in cloud or office environments. Both roles require strong analytical skills but differ in technical focus and work settings.

What are some common challenges faced by Remote Embedded Machine Learning Engineers, and how can they be addressed?

Remote Embedded Machine Learning Engineers often encounter challenges related to hardware access, debugging embedded devices remotely, and collaborating with cross-functional teams across time zones. To address these, it's important to set up robust remote development environments, use simulation tools when physical hardware isn't available, and establish clear communication channels for effective teamwork. Regular virtual meetings and detailed documentation also help ensure alignment and smooth progress, despite the remote nature of the work.
What cities in Georgia are hiring for Remote Embedded Machine Learning jobs? Cities in Georgia with the most Remote Embedded Machine Learning job openings:
Staff Machine Learning Engineer

Staff Machine Learning Engineer

PrizePicks

Atlanta, GA โ€ข On-site, Remote

$220K - $280K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 8 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.