Voice Recognition

Voice Recognition Data Jobs

3 jobs found

Today

Sr. Machine Learning Engineer

AppFolio Columbus, OH

Columbus, OH

Today

$167k - $209k/yr Full time Senior Agent Orchestration Agentic Ai

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Job Description

Design and ship low-latency voice and conversational AI agent pipelines within Realm-X.

Responsibilities

Architect and deliver voice and text agent pipelines for real-time, multi-turn customer interactions
Evaluate and implement principled trade-offs across frontier LLMs, smaller models, and routing strategies with a focus on reasoning depth vs latency
Lead a small pod of ML and platform engineers; improve agent evaluation, observability, and incident response
Work with Product and Voice channel teams to define KPIs, eval harnesses, and acceptance criteria for agent quality
Drive selective SLM fine-tuning and inference optimization to improve voice latency and cost

Requirements

Deep, shipped experience with LangChain, LangGraph, LangSmith, and LangChain Deep Agents (or equivalent agent frameworks)
Hands-on with Voice-to-Voice models plus traditional TTS / STT pipelines; understands end-to-end voice models vs modular STT + LLM + TTS trade-offs
Strong grasp of LLM behavior for reasoning, tool use, structured output, and reasoning vs latency trade-offs across providers
Production experience with Twilio (or comparable telephony) and AWS
Expert Python, async programming, and WebSockets for real-time, bidirectional streaming
Solid foundation in deep learning, model evaluation, and inference optimization; deploy with Docker on AWS
Proven ability to lead a small team, mentor engineers, and partner credibly with Product and Design
Shipped production AI agents serving real users in voice and/or text channels
Think in pipelines and systems, not only models
Move fast, deliver impact, and maintain sound engineering judgment
Work with humility and collaboration; low-ego leadership and strong team elevation
Values work-life balance as a foundation for sustained high performance

Technologies

LangChain, LangGraph, LangSmith, LangChain Deep Agents
Voice-to-Voice models, TTS, STT
Twilio, AWS
Python, WebSockets
Docker

Nice to Have

Experience fine-tuning Small Language Models for domain-specific voice applications
Familiarity with RAG over structured business data and tool-using agents over API surfaces
Prior experience in regulated or customer-facing industries with strict reliability requirements
Publicly verifiable work on GitHub, in open-source agent frameworks, or in community competitions

Location

Columbus, OH (onsite)
Late-stage candidates complete an in-person meeting with an AppFoliOian as part of the hiring process

Compensation & Benefits

Base pay range: USD 167,200 - 209,000 per year
Final compensation determined by skills, education, experience, and internal equity
Regular full-time employees are eligible for benefits
The listed compensation range excludes additional benefits and any discretionary bonuses
#LI-KB1

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2d ago

Audio AI Engineer

Dev Technology Reston, VA

Reston, VA

2d ago

$80k - $160k/yr Full time Ai Engineer Artificial Intelligence Asr

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Job Description

Build and optimize a speech-to-text core that powers mobile translation performance on iPhone-class devices.

Responsibilities

Ingest, clean, segment, label, and version multilingual audio and transcript data, with focus on code-switching and borrowed-word behavior across the target language set.
Fine-tune and compress large ASR models to meet iPhone memory, latency, and battery constraints while preserving transcription quality.
Apply parameter-efficient and size-reduction approaches such as LoRA/QLoRA, quantization, distillation, and/or other techniques as appropriate.
Design packaging and on-demand language selection so language-specific weights can be downloaded based on context (for example, selecting Chinese ASR weights when an operator interviews a Chinese speaker).
Build and evaluate decision logic for borrowed English terms: transcribe as-is versus output as transliteration or a native equivalent in the source language.
Create reproducible evaluation pipelines using metrics such as word error rate and character error rate, plus latency and robustness checks (accent, noise, speaking rate, and code-switching).
Communicate results against defined success criteria for each language and deployment target.
Write clear model cards, dataset documentation, and evaluation write-ups for technical and non-technical stakeholders, including what the model does, comparisons to alternatives, and risks/limitations.

Requirements

Bachelor's degree in Computer Science, Data Science, Machine Learning, Computational Linguistics, or a closely related field.
Strong data-engineering background building production pipelines for large, messy, or unstructured audio/text datasets.
Hands-on experience fine-tuning or adapting speech/audio models using parameter-efficient methods (LoRA, QLoRA, adapters) and/or compression techniques (quantization, distillation, pruning) for constrained hardware.
Practical experience developing and evaluating ASR/speech-to-text systems across multiple languages, including error analysis under real-world conditions (accents, noise, code-switching).
Strong Python and SQL skills; experience with PyTorch, Hugging Face Transformers/PEFT, torchaudio, librosa, or comparable tooling.
Experience deploying and monitoring production ML systems, including secure handling of sensitive audio, transcripts, and derived data in regulated environments.
Ability to explain model behavior, tradeoffs, and limitations to both technical and non-technical stakeholders.

Technologies

Python, SQL
PyTorch
Hugging Face Transformers, PEFT
torchaudio, librosa
LoRA, QLoRA
Quantization, distillation, pruning
iPhone, iOS
Swift, AVFoundation

Benefits

Generous and flexible time-off policy
Flexible work schedules and telework options, including remote work availability for eligible projects
Career development: mentorship program, Dev University technical and management training, DevLab hands-on learning, tuition reimbursement, and paid training opportunities
Industry-leading benefits including choice of two health plans with dental and vision, flexible spending account, commuter benefits, life insurance, and more
401K matching with a 5% matching contribution
Regular team and company social events (annual party, happy hours, fitness challenges, and more)
Community engagement: company-wide support activities, employer match for donations, and time off for volunteer efforts

Compensation: USD 80,000 - 160,000 per year.

Location: Reston, VA (onsite).

What this role is (and isn’t):

Owns the speech-to-text model: data, training/adaptation, model size and latency on-device, and transcription accuracy across languages.
Does not own iOS application development, translation (source-language to target-language), or the Swift/AVFoundation integration layer. Those are handled by a separate mobile engineering function this role will collaborate with.

Preferred (not required)

Prior exposure to mobile/on-device ML deployment constraints, even without owning the mobile codebase directly.
Experience with agentic or multi-step workflow orchestration involving model outputs, retrieval, or human review.

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4d ago

Sr. Machine Learning Engineer

AppFolio Atlanta, GA

Atlanta, GA

4d ago

$167k - $209k/yr Full time Senior Agentic Ai Artificial Intelligence

Apply Now

Job Description

AppFolio is hiring a Senior Machine Learning Engineer in Atlanta, GA (onsite) to design and ship voice and conversational AI agents within Realm-X. In this role, you will build production agent pipelines and focus on practical delivery: balancing LLM reasoning with low-latency streaming across multi-channel customer experiences.

This position is a strong fit if you enjoy turning agent concepts into reliable systems, partnering with Voice and Product teams on measurable quality, and iterating quickly while maintaining sound engineering judgment.

What you’ll do

Architect and ship voice and text agent pipelines for real-time, multi-turn customer interactions.
Make principled trade-offs between reasoning depth and latency across frontier LLMs, smaller models, and routing strategies.
Lead a small pod of ML and platform engineers, raising the bar on agent evaluation, observability, and incident response.
Partner with Product and Voice channel teams to define KPIs, build evaluation harnesses, and set acceptance criteria for agent quality.
Drive selective SLM fine-tuning and inference optimization to improve voice latency and cost.

What you’ll bring

Deep, shipped experience with LangChain, LangGraph, LangSmith, and LangChain Deep Agents (or equivalent agent frameworks).
Hands-on experience with Voice-to-Voice models and traditional TTS / STT pipelines, including understanding trade-offs between end-to-end voice models and modular STT LLM TTS architectures.
Strong grasp of LLM reasoning behavior, tool use, structured output, and reasoning-vs-latency trade-offs across providers.
Production experience with Twilio (or comparable telephony) and AWS.
Expert Python, async programming, and WebSockets for real-time, bidirectional streaming.
Solid foundation in deep learning, model evaluation, and inference optimization; ability to deploy with Docker on AWS.
Demonstrated ability to lead a small team, mentor engineers, and partner credibly with Product and Design.
Experience shipping production AI agents serving real users in voice and/or text channels.
Systems thinking, fast execution with impact, and strong engineering judgment; ability to collaborate with a low-ego, humble, and inclusive approach.
Values work-life balance as a foundation for sustained high performance.

Nice to have

Experience fine-tuning Small Language Models for domain-specific voice applications.
Familiarity with RAG over structured business data and tool-using agents over API surfaces.
Prior experience in regulated or customer-facing industries with strict reliability requirements.
Publicly verifiable work on GitHub, in open-source agent frameworks, or in community competitions.

Technologies you’ll use

LangChain, LangGraph, LangSmith, LangChain Deep Agents
Voice-to-Voice models, TTS, STT
Twilio, AWS, Python, async programming, WebSockets, Docker
LLM, Small Language Model (SLM), RAG

Compensation & benefits

Base pay: USD 167,200 - 209,000 per year.

The actual compensation will be determined by factors including skills, education, experience, and internal equity. Compensation is part of a broader Total Rewards package and the range listed does not include additional benefits or any discretionary bonuses.

Regular full-time employees are eligible for benefits.

#LI-KB1

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Voice Recognition Data Jobs

Sr. Machine Learning Engineer

Audio AI Engineer

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