1

Edge Ai Machine Learning Jobs in Columbia, SC (NOW HIRING)

We're looking for engineers fluent in modern AI application development - agent frameworks, harnesses, tool use, prompting, retrieval, and evaluation - not machine learning engineers. You will be ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... Responsibilities - Work with cross-functional teams to incorporate AI into various applications ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... The Opportunity As part of the People Tech & AI team you will lead the design, build, and operation ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... AI solutions that drive remarkable client outcomes. As a Manager you will supervise, develop, and ...

Data Science Tutor

Columbia, SC · Remote

$18 - $40/hr

Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

Showing results 21-40

Edge Ai Machine Learning information

See Columbia, SC salary details

$23.6K

$39.4K

$81.4K

How much do edge ai machine learning jobs pay per year?

As of Aug 18, 2026, the average yearly pay for edge ai machine learning in Columbia, SC is $39,396.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,100.00 and $42,600.00 per year, depending on experience, location, and employer.

What is an Edge AI Machine Learning?

An Edge AI Machine Learning job involves developing and deploying machine learning models directly on edge devices, such as IoT sensors, mobile devices, and embedded systems. This role requires expertise in optimizing AI models for low-power, low-latency environments while ensuring real-time processing. Professionals in this field work with frameworks like TensorFlow Lite, ONNX, and OpenVINO to implement AI solutions efficiently. They must also handle challenges like model compression, hardware acceleration, and data privacy.

What are the key skills and qualifications needed to thrive in the Edge AI Machine Learning position?

To thrive as an Edge AI Machine Learning professional, you need a strong background in machine learning algorithms, embedded systems, and proficiency with programming languages such as Python or C++. Familiarity with edge computing platforms (like NVIDIA Jetson, Google Coral), frameworks (TensorFlow Lite, ONNX), and certifications in AI or ML can greatly enhance your qualifications. Strong problem-solving abilities, collaboration, and effective communication skills are important for adapting solutions to diverse environments and working cross-functionally. These abilities enable the successful deployment of efficient and robust AI models directly on devices, meeting the unique challenges of real-time, resource-constrained settings.

What are some typical challenges faced in an Edge AI Machine Learning role, and how can I prepare for them?

One of the most common challenges in Edge AI Machine Learning is optimizing models to run efficiently on hardware with limited resources, while maintaining acceptable accuracy and speed. You may encounter constraints related to memory, processing power, and connectivity, which require creative engineering and a deep understanding of both machine learning and embedded systems. Collaborating closely with hardware engineers, data scientists, and software developers is typical, as solutions often span multiple technical disciplines. To prepare, staying current with advancements in model compression, quantization, and edge deployment technologies will help you tackle these challenges with confidence.

What are popular job titles related to Edge Ai Machine Learning jobs in Columbia, SC?

For Edge Ai Machine Learning jobs in Columbia, SC, the most frequently searched job titles are:

What job categories do people searching Edge Ai Machine Learning jobs in Columbia, SC look for?

The top searched job categories for Edge Ai Machine Learning jobs in Columbia, SC are:

What cities near Columbia, SC are hiring for Edge Ai Machine Learning jobs?

Cities near Columbia, SC with the most Edge Ai Machine Learning job openings:

Senior Software Engineer Applied AI

Advanced Monitored Caregiving Inc.

Columbia, SC • Remote

$113K - $149K/yr

Full-time

Re-posted 4 days ago


Job description

Senior Software Engineer: Applied AI (Voice Agents & ML Systems)

AMC Health · Remote (US) · Full-time

The pitch

We build and operate production AI voice agents that hold real phone conversations in a regulated healthcare setting, plus the machine learning and LLM pipelines around them. This is one seat that spans four disciplines that rarely come together: real-time systems, LLM engineering, traditional machine learning, and serious cloud infrastructure, all in production, all with real consequences. If you are the kind of engineer who gets restless doing one thing, this role is the opposite problem.

What you'll work across

Real-time voice AI

  • Streaming, low-latency speech-to-speech systems built on modern LLMs
  • Telephony and real-time media (call control, live audio streaming)
  • Audio handling and the quirks of real human conversation (interruptions, timing, noise)
  • Concurrency on a latency-sensitive path, where p99 matters and a stall is something a caller hears

LLM engineering

  • Wrapping nondeterministic models in deterministic control so they behave reliably in production
  • Multi-model pipelines, prompt design, and cost/latency budgeting
  • Evaluation harnesses, including LLM-as-judge and automated agent-tests-agent approaches
  • Agentic tooling that gives AI systems safe, structured access to infrastructure

Traditional (non-LLM) machine learning

  • End-to-end ML pipelines: feature engineering, model training, and scheduled inference
  • Imbalanced, messy real-world data; calibration and explainability for non-technical consumers
  • Turning research notebooks into reproducible, auditable production pipelines

Cloud and infrastructure

  • Infrastructure as code across multiple environments (we run on AWS)
  • Managed compute, data, streaming, and orchestration services
  • Security engineering in a regulated setting: encryption, least-privilege access, strict data-handling discipline
  • Observability and telemetry-driven debugging, tracing a production issue from a metric anomaly to root cause

Plus occasional full-stack work on internal tools, and an engineering workflow that leans heavily on AI coding assistants, with human accountability for every change.

What you'll actually do

  • Ship and debug code on a live, real-time voice pipeline where latency and correctness are user-facing
  • Design control systems around LLMs: guardrails, budgets, watchdogs, safe fallbacks
  • Build and operate LLM evaluation and batch-analysis pipelines
  • Own traditional ML workflows from data to scheduled production inference
  • Trace production issues from a metric anomaly to root cause, including building the evidence when the cause is a vendor

Must-haves

  • 7+ years building and operating production backend systems, with strong general-purpose programming skills (we work primarily in Python)
  • Experience running distributed systems in the cloud; comfortable debugging from telemetry to root cause
  • Hands-on production experience with LLMs or generative AI (any provider or framework), plus the judgment to know when not to use a model
  • Working fluency across the traditional machine learning lifecycle (you productionize; you do not need to publish)
  • Disciplined in a regulated environment: small, reviewable changes and careful handling of sensitive data

Nice-to-haves

  • Real-time media or telephony experience
  • Front-end / full-stack ability
  • ML pipeline experience, vector search, or embeddings
  • Fluency with AI coding assistants (our workflows assume them, with human accountability for every change)

How we work

Smallest correct change wins. Every behavior change is validated against the live system. Evidence over opinion in debugging. Code review is rigorous. Safety and privacy gate everything.

Work authorization (no exceptions)

This role is open only to US citizens and lawful permanent residents (Green Card holders). We cannot consider candidates who require visa sponsorship now or in the future, and we are unable to make exceptions of any kind.

How to apply

Please submit both of the following:

  • Your LinkedIn profile URL
  • A phone number where we can reach you

A resume is welcome but optional; the two items above are required.