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Full Duplex Jobs (NOW HIRING)

Rime Labs

Forward Deployed Engineer

San Francisco, CA · On-site

So before we trained a single model, we built our own corpus: full-duplex, studio-quality conversational speech, recorded and annotated by PhD linguists. That's our moat. It's also why enterprises ...

Rime Labs

Founding Account Executive

San Francisco, CA · On-site

So before we trained a single model, we built our own corpus: full-duplex, studio-quality conversational speech, recorded and annotated by PhD linguists. That's our moat. It's also why enterprises ...

Hark

Audio Quality and Data Engineer

San Jose, CA · On-site

$84K - $109K/yr

Experience evaluating LLM-based voice agents or full-duplex conversational systems (turn-taking, interruption handling, end-pointing, latency budgets). * Familiarity with ASR evaluation methodology ...

Comcast

Comcast Product Analyst Co-op

Philadelphia, PA · On-site

The overall workflow orchestration and data assets are critical to supporting our yearly target to upgrade ~10 million addresses to full duplex speeds and 1.25 million net new serviceable addresses.

Hark

Audio Quality and Data Engineer

San Jose, CA · On-site

$84K - $109K/yr

Experience evaluating LLM-based voice agents or full-duplex conversational systems (turn-taking, interruption handling, end-pointing, latency budgets). * Familiarity with ASR evaluation methodology ...

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All JobsFull Duplex Jobs

Full Duplex information

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$759

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How much do full duplex jobs pay per week?

As of Jun 12, 2026, the average weekly pay for full duplex in the United States is $2,116.79, according to ZipRecruiter salary data. Most workers in this role earn between $1,557.69 and $2,634.62 per week, depending on experience, location, and employer.

What is the difference between Full Duplex vs Half Duplex?

FeatureFull DuplexHalf Duplex
Communication TypeSimultaneous two-way communicationOne direction at a time
Work EnvironmentTelecommunications, networking, radio systemsRadio communication, walkie-talkies
Required CredentialsNetworking certifications, technical knowledgeBasic communication skills, technical understanding

Full Duplex allows for simultaneous two-way communication, making conversations seamless. Half Duplex only permits one direction at a time, requiring users to switch between transmitting and receiving. Both are used in communication systems, but Full Duplex is preferred for real-time, continuous conversations, especially in networking and telecommunications.

What is the 3 month rule for jobs?

The 3 month rule in the context of Full Duplex jobs often refers to a probation or trial period lasting approximately three months, during which employers assess a new employee’s performance and fit for the role. This period may influence decisions on continued employment, benefits, or permanent status, and some companies require employees to complete this timeframe before becoming eligible for certain perks or job security. Skills such as communication and adaptability are typically evaluated during this period.

What jobs make $10,000 a month without a degree?

Full Duplex roles in sales, real estate, or skilled trades can sometimes earn $10,000 or more monthly through commissions, bonuses, or high hourly rates. These jobs often require strong communication skills, experience, or certifications but do not necessarily require a college degree.

What jobs make around $100,000 a year?

Full Duplex roles in fields like engineering, software development, and management can offer salaries around $100,000 annually, especially with experience and specialized skills. Positions such as software engineers, project managers, and technical leads often reach this level, particularly in high-demand industries or with advanced certifications. Salary ranges vary based on location, industry, and experience, but these roles are commonly associated with six-figure compensation.

What jobs pay 2000 a day?

High-paying jobs that can pay around $2,000 a day typically include specialized roles such as senior corporate executives, certain medical specialists, high-level consultants, and experienced freelance professionals in fields like software development or finance. These positions often require advanced skills, extensive experience, and sometimes certifications, and may involve project-based or contract work with high hourly or daily rates.
Infographic showing various Full Duplex job openings in the United States as of June 2026, with employment types broken down into 78% Full Time, and 22% Part Time. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $110,073 per year, or $52.9 per hour.

Machine Learning Engineer, Data Quality

Rime Labs

San Francisco, CA

$134K - $162K/yr

Other

Posted 16 days ago

Job description

Machine Learning Engineer, Data Quality
Rime builds voice AI for enterprises running customer experiences at scale. Our text-to-speech models are purpose-built for high-volume conversational deployments, engineered for the pronunciation accuracy, latency, and deployment flexibility that production environments actually demand.
We started from a different premise than the rest of the field: voice AI isn't bottlenecked by model architecture. It's bottlenecked by data. So before we trained a single model, we built our own corpus: full-duplex, studio-quality conversational speech, recorded and annotated by PhD linguists. That's our moat. It's also why enterprises pick Rime when pilots need to convert into production.
We're backed by top-tier investors including Unusual Ventures, and we've built a team at the intersection of product, research, and craft. Building voice models is an art. We intend to master it. The path is the craft itself: the loop between theory and practice - the shared mental model of how things should behave, met by the reality that doesn't quite conform, sharpened by the meeting.
Role Overview
We're hiring a Machine Learning Engineer, Data Quality to own the operational data pipeline that produces our training corpus end-to-end - and to bring a vision for where it should go next. We take that seriously: if you can plan an overhaul, justify it, and orchestrate the human and machine migration work, we'll do it together.
This is a sociotechnical role. You'll be in the loop on everything and talking to everyone that touches the data across 42+ languages: 50+ annotators, 32+ external vendors and an in-house recording studio, and the systems behind them - ingestion, quality assurance, pre-processing, cataloging, export to training. At any given moment, dozens of deliverables are in flight, each on its own clock.
The people who thrive here want to listen to the audio clips and design the system that scales their judgment to the next million. You don't need deep expertise across the whole stack on day one - you need the judgment to know what good looks like at each stage, and the engineering depth to build (or learn to build) the parts that need building.
What You'll Own
  • Linguist- and annotation-team-facing tooling: annotation UI, PM workflow for project management, QC dashboards. This is the surface the frontline uses every day.
  • Vendor data QA workflows: A large share of incoming data arrives from vendors in various states and needs to pass QA before it can be trusted. The tooling, routing, and tracking for that work is yours.
  • Quality systems across the network: The signals, dashboards, and review loops that surface when a corner of the network is drifting - a vendor's transcripts getting sloppy, an annotator's IAA slipping, a language's gold set going stale - before it lands in the training pool.
  • End-to-end audio annotation pipeline: Currently some stages exist as prototypes; productionizing and rebuilding them is work that's currently in flight.
  • Dataset versioning and experimenter tooling: the model team will want to subset the vetted pool ("speakers X/Y/Z, duration 3-12s, quality > 0.8") into reproducible training manifests. The query interface, manifest format, and lineage tracking are all yours.
  • Pipelines for full- and half-duplex training data
What We're Looking For
  • Instinct for data quality. You can tell good data from bad. You know what "bad" looks like in this specific domain - not just generic "anomalies," but the particular ways audio and transcripts go wrong.
  • Willing to look at the data. Open the file. Listen to the clip. Read the transcript. You don't outsource the first-pass checks to a script.
  • Opinionated, and curious when challenged. You arrive with a perspective informed by what you've seen work and what you've seen fail - and you're equally interested in pressure-testing it. A "what about..." question isn't a threat; it's where the work happens.
  • Project sense. You can hold a lot of moving parts in your head - what's in flight, what's blocked, what's about to slip - and keep the picture clear enough that others can step into it.
  • Designs, doesn't just execute. You want to take on more design responsibility over time, not less. You're looking for a role where you (co-)own things end-to-end, not one where someone hands you tasks to implement.
  • Comfort being out of your depth at the boundary. You'll sometimes debug code you didn't write in tools you don't use daily. You should find this energizing, not threatening.
  • Solid software and data engineering fundamentals. Python, schemas you can reason about, production data pipelines you've built and operated on cloud-native infrastructure.
Nice to have - in rough order from hardest-to-acquire to most learnable:
  • Audio pipeline tooling: ffmpeg, Silero VAD, faster-whisper, neural audio codecs (Encodec, SNAC, SoundStream).
  • TTS frontend work: G2P (phonemizer, g2p-en), text normalization (NeMo TN or equivalent), prosody and phoneme alignment.
  • Annotation platforms: Label Studio, Argilla, or equivalent - particularly customizing or replacing them.
  • Direct experience with our stack: GCP (Cloud Run, Cloud Batch, GCS, Pub/Sub), Supabase / Postgres. AWS or Azure experience maps fine.
Why Join Rime
  • Build the data infrastructure behind a category-defining voice AI company.
  • The pipelines you build determine what models we can train.
  • Meaningful equity upside.
  • High ownership, high standards, low bureaucracy.
What We Offer
  • Competitive base + meaningful early-stage equity
  • Remote-friendly
  • Visa sponsorship available
  • Access to a proprietary, full-duplex, studio-quality conversational speech corpus
  • Compute and tooling to do the work
  • Direct influence on the future of voice AI
At Rime, we...
  • Are outliers
  • Cut through the hype to focus on the craft
  • Move fast with agency and freedom
  • Maintain a growth mindset, finding joy in the struggle
  • Do the right things, knowing that it'll lead to making money

If that sounds like you too, you'll be a great fit for Rime!

Apply