ZipRecruiter

Log In

1

Temporary Computer Vision Deep Learning Engineer Jobs in Georgia

AppFolio

Sr. Machine Learning Engineer

GA · Remote

$100.50K - $138K/yr

... the technical vision and architecture for AI systems within Realm-X * Design and build deep ... D. in Computer Science, Machine Learning, or a related technical field (required) * Extensive ...

AppFolio

Sr. Machine Learning Engineer

Atlanta, GA · Remote

$100.50K - $138K/yr

... the technical vision and architecture for AI systems within Realm-X * Design and build deep ... D. in Computer Science, Machine Learning, or a related technical field (required) * Extensive ...

Dolby

Sr. Foundational Audio AI Researcher

Atlanta, GA · On-site

... engineering, image processing, computer vision, data science & analytics, distributed systems ... D. in Computer Science or similar field. • A strong background in deep learning, both in terms of ...

Fisec Global

Gen AI Engineer

Atlanta, GA · On-site

Strong background in machine learning, deep learning, and probabilistic modeling. * Proficiency in ... Strong programming skills in Python and experience working with version control systems (Git)

AEG

Staff Machine Learning Engineer

Atlanta, GA · On-site

$220K - $280K/yr

Deep experience managing the full ML lifecycle (training, deploying, monitoring) using tools like ... Company-subsidized medical, dental, & vision plans * 401(k) plan with company match * Annual bonus

next page

Showing results 1-20

People also search for

All JobsTemporary Computer Vision Deep Learning Engineer JobsTemporary Computer Vision Deep Learning Engineer Jobs in Georgia

Temporary Computer Vision Deep Learning Engineer information

What is the difference between Temporary Computer Vision Deep Learning Engineer vs Computer Vision Engineer?

AspectTemporary Computer Vision Deep Learning EngineerComputer Vision Engineer
CredentialsBachelor's or Master's in CS, AI, or related; experience with deep learning frameworksBachelor's or Master's in CS, AI, or related; experience with computer vision tools
Work EnvironmentProject-based, short-term contracts, often in tech or research firmsFull-time, ongoing roles in tech companies, startups, or research labs
Industry UsageCommon in consulting, research projects, or temporary assignmentsStandard role in product development, AI solutions, and software engineering

The main difference is that a Temporary Computer Vision Deep Learning Engineer works on short-term projects focusing on deep learning techniques for computer vision, while a Computer Vision Engineer typically holds a permanent position involved in ongoing development of computer vision applications. The temporary role emphasizes flexibility and project-specific skills, whereas the full-time role involves continuous integration into a company's long-term projects.

What are the most commonly searched types of Computer Vision Deep Learning Engineer jobs in Georgia? The most popular types of Computer Vision Deep Learning Engineer jobs in Georgia are:
What are popular job titles related to Temporary Computer Vision Deep Learning Engineer jobs in Georgia? For Temporary Computer Vision Deep Learning Engineer jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Temporary Computer Vision Deep Learning Engineer jobs in Georgia look for? The top searched job categories for Temporary Computer Vision Deep Learning Engineer jobs in Georgia are:
What cities in Georgia are hiring for Temporary Computer Vision Deep Learning Engineer jobs? Cities in Georgia with the most Temporary Computer Vision Deep Learning Engineer job openings:
Temporary Computer Vision Deep Learning Engineer jobs near you
Infographic showing various Temporary Computer Vision Deep Learning Engineer job openings in Georgia as of May 2026, with employment types broken down into 1% As Needed, 77% Full Time, 17% Part Time, 1% Temporary, and 4% Contract. Highlights an 91% Physical, 1% Hybrid, and 8% Remote job distribution.

Sr. Machine Learning Engineer

AppFolio

Remote

$100.50K - $138K/yr

Full-time

Posted 24 days ago

Job description

Hi, We’re AppFolio
We’re innovators, changemakers, and collaborators. We’re more than just a software company — we’re building the cloud and AI-native platform where the real estate industry comes to do business. We’re revolutionizing how property managers operate, how residents live, and how intelligence flows through an entire industry.
We are now building the next generation of our platform with AI at the core.
Realm-X is AppFolio’s AI platform powering this transformation:
  • Assistant: a GenAI copilot embedded across the product experience
  • Flows: an agentic workflow system enabling automation of complex business processes
  • Performers: real-time, multi-modal AI agents operating across voice, text, email, and chat
We are building not only these experiences, but also the platform that enables teams across AppFolio to contribute and extend AI capabilities.
At the foundation are deep agents, built on a real estate ontology and domain primitives (transactions, actions, reports, metrics, and skills), allowing AI systems to understand and operate across the full business context of AppFolio — powering both employee productivity and end-to-end automation.
Who we are looking for
We’re seeking a Sr Machine Learning Engineer to play a critical role in shaping Realm-X and the future of AI at AppFolio.
This is a high-impact position focused on defining architecture, building next-generation AI systems, and influencing technical direction across teams. You will work at the intersection of machine learning, distributed systems, and product innovation to create AI systems that move beyond assistance into execution.
Responsibilities:
  • Define and drive the technical vision and architecture for AI systems within Realm-X
  • Design and build deep, context-aware agents leveraging domain ontologies and structured business primitives
  • Lead the development of agentic workflows (Flows) that combine reasoning, planning, and execution
  • Architect systems for real-time, multi-modal AI agents (Performers) across communication channels
  • Build and evolve platform capabilities (tools, memory, evaluation systems, abstractions) to enable broad internal adoption
  • Translate ambiguous, high-impact problems into scalable, production-ready AI systems
  • Establish best practices for LLM evaluation, observability, safety, and iteration loops
  • Collaborate cross-functionally with product, design, and engineering leaders to shape strategy and execution
  • Mentor engineers and raise the technical bar across the organization
  • Identify and introduce emerging AI technologies and paradigms that create leverage for the business
You know you’re the right fit if…
  • You think in terms of systems and platforms, not just features
  • You have a track record of building and deploying ML/AI systems in production at scale
  • You are comfortable operating in high ambiguity and defining direction where none exists
  • You can lead through influence, aligning multiple teams around a technical vision
  • You balance long-term architecture with pragmatic delivery
  • You are motivated by high-impact problems that shape products and business outcomes
Additional Skills and Knowledge:
  • Master’s or Ph.D. in Computer Science, Machine Learning, or a related technical field (required)
  • Extensive experience developing and deploying machine learning systems in production environments
  • Strong software engineering expertise with languages such as Python, Go, Ruby, or JavaScript
  • Deep understanding of distributed systems, APIs, and cloud infrastructure (AWS or similar)
  • Experience leading large, cross-functional technical initiatives
  • Ability to design systems that integrate structured data, models, and real-time decisioning
Nice to Have:
  • Experience with LLMs, AI agents, and tool-using systems (e.g., LangChain, LangGraph, OpenAI APIs)
  • Familiarity with agentic architectures, planning/execution loops, and orchestration frameworks
  • Experience building domain-specific ontologies, knowledge graphs, or semantic layers evaluation frameworks for AI systems (offline and online)
  • Background in workflow orchestration systems (e.g., Temporal)
  • Experience building platforms that enable other engineering teams
  • Exposure to multi-modal AI systems (voice, chat, email, etc.)
Compensation & Benefits
The compensation that we reasonably expect to pay for this role is: 167,200.00 - 209,000.00 base pay. The actual compensation for this role will be determined by a variety of factors, including but not limited to the candidate’s skills, education, experience, and internal equity.
Please note that compensation is just one aspect of a comprehensive Total Rewards package. The compensation range listed here does not include additional benefits or any discretionary bonuses you may be eligible for based on your role and/or employment type.
Regular full-time employees are eligible for benefits - see here.

#LI-KB1

Apply