ZipRecruiter

Log In

1

Freelance Audio Machine Learning Jobs in Maryland

Avancer Corporation

Lead AI Engineer

Rockville, MD · On-site

$104K - $137K/yr

... audio, and video. * Build multimodal extraction using OCR, layout parsing, and vision-language ... Experience Requirements * 8+ years in software engineering or machine learning with production AI ...

Amtex System Inc.

Lead AI Engineer

Rockville, MD · On-site

$104K - $137K/yr

... audio, and video. * Build multimodal extraction using OCR, layout parsing, and vision-language ... Experience Requirements: * 8+ years in software engineering or machine learning with production AI ...

Amtex Systems Inc

Lead AI Engineer

Rockville, MD · On-site

$104K - $137K/yr

... audio, and video. * Build multimodal extraction using OCR, layout parsing, and vision-language ... Experience Requirements: * 8+ years in software engineering or machine learning with production AI ...

next page

Showing results 1-20

All JobsAudio Machine Learning JobsFreelance Audio Machine Learning JobsFreelance Audio Machine Learning Jobs in Maryland

Freelance Audio Machine Learning information

What is the difference between Freelance Audio Machine Learning vs Freelance Audio Signal Processing?

AspectFreelance Audio Machine LearningFreelance Audio Signal Processing
Required SkillsMachine learning, programming, audio analysisDigital signal processing, audio engineering, software tools
Work EnvironmentData analysis, model development, algorithm designAudio editing, filtering, signal enhancement
Common EmployersTech companies, startups, research labsAudio production houses, broadcasting, music industry
CertificationsMachine learning, data science, programming certificationsAudio engineering, DSP certifications

Freelance Audio Machine Learning focuses on developing algorithms and models to analyze and interpret audio data using machine learning techniques. In contrast, Freelance Audio Signal Processing involves applying traditional digital signal processing methods to enhance or modify audio signals. Both roles require technical expertise but differ in their core methods and applications.

What are the most commonly searched types of Audio Machine Learning jobs in Maryland? The most popular types of Audio Machine Learning jobs in Maryland are:
What are popular job titles related to Freelance Audio Machine Learning jobs in Maryland? For Freelance Audio Machine Learning jobs in Maryland, the most frequently searched job titles are:
What job categories do people searching Freelance Audio Machine Learning jobs in Maryland look for? The top searched job categories for Freelance Audio Machine Learning jobs in Maryland are:
What cities in Maryland are hiring for Freelance Audio Machine Learning jobs? Cities in Maryland with the most Freelance Audio Machine Learning job openings:
Freelance Audio Machine Learning jobs near you

Senior Software Engineer Applied AI

Advanced Monitored Caregiving Inc.

Annapolis, MD • On-site

$140 - $180/hr

Other

Posted 28 days ago

Job description

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

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

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

#J-18808-Ljbffr

Apply