Director of Product Management, Agentforce Voice Models

salesforce.com, inc.; San Francisco (CA); On-site; USD 197,000 - 314,000; Full time

Job summary

Salesforce is seeking a Director of Agentforce Voice Models to own the full voice intelligence stack—ASR/STT, TTS, S2S, speaker diarization, and language coverage. You will partner with product, infra, and GTM teams to set high-accuracy, low-latency voice capabilities at enterprise scale.

You will recruit and lead a 20–30 person team of researchers and ML engineers, driving architectural excellence, ethical considerations, and market-leading voice experiences across languages and markets.

Qualifications

• Over 10 years in speech/audio ML with leadership of 10+ engineers/scientists.
• Hands-on expertise in ASR, neural TTS, or real-time speech processing.
• Experience shipping production voice models at enterprise scale.

Responsibilities

• Own voice model strategy and multi-year roadmap for Agentforce voice.
• Define accuracy, latency, and quality benchmarks across ASR, TTS, S2S.
• Lead engineering teams and drive architectural decisions for voice AIs.
• Collaborate with Product, Legal, Privacy, and Trust teams on ethics and compliance.

Skills

Speech ML leadership

ASR / STT

TTS

S2S / real-time voice

Multilingual voice NLP

Python

PyTorch / JAX

Cloud training infra

Communication to executives

Education

PhD in CS/EE/Linguistics (speech focus)

Tools

Genesys

NICE

Avaya

Amazon Connect

SIP / RTP / WebRTC

Job description

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.

Job Category

Product

Job Details

About Salesforce

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword - it’s a way of life. The world of work as we know it is changing and we’re looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce’s core values at the heart of it all.

Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.

About the Role

Agentforce is Salesforce’s next-generation AI platform, delivering autonomous agents that reason, take action, and communicate naturally across every customer touchpoint.

Voice is the fastest-growing interaction surface-from contact-center automation and field-service assistants to real-time sales coaching and multilingual global deployments.

As Director of Agentforce Voice Models, you will own the full voice intelligence stack: Automatic Speech Recognition (ASR / STT), Text-to-Speech (TTS), Speech-to-Speech (S2S) end-to-end pipelines, speaker diarization, prosody modeling, and the language-coverage roadmap that makes Agentforce sound natural in every market we serve. You will partner with product, infrastructure, and go-to-market teams to set the bar for transcription accuracy, latency, and voice expressiveness at enterprise scale.

Voice Model Strategy & Roadmap

• Define and own the multi-year roadmap for Agentforce voice capabilities, spanning ASR/STT, TTS, S2S, and real-time voice agents.
• Set accuracy, latency, and quality benchmarks (WER, MOS, RTF, DMOS) and drive the organization to meet them.
• Evaluate build vs. buy vs. partner decisions for new voice model capabilities and maintain relationships with key academic and industry partners.

ASR / STT (Automatic Speech Recognition)

• Lead the development of production-grade ASR systems optimized for telephony, WebRTC, and device-side deployment. Word Error Rate (WER) improvement across noise conditions, accents, and domain-specific vocabulary. Streaming and batch recognition pipelines with sub-200 ms first-token latency targets. Custom vocabulary and language model adaptation (hot-word boosting, domain LM interpolation). Punctuation restoration and inverse text normalization (ITN) for downstream NLU.
• Drive multilingual and code-switching ASR coverage across priority languages; govern the language onboarding process including data acquisition, model training, and acceptance testing.

TTS (Text-to-Speech)

• Own the neural TTS pipeline-voice cloning, persona design, SSML compliance, and real-time synthesis-for Agentforce agent personas.
• Lead prosody research: intonation, rhythm, stress, and pause modeling that produces natural-sounding enterprise voices across conversational contexts.
• Manage voice talent agreements, ethical AI review, and consent frameworks for synthetic voice creation.
• Drive naturalness, expressiveness, and brand-consistency quality bars using subjective (MOS, CMOS) and objective (mel-cepstral distortion) evaluation frameworks.

Speech-to-Speech (S2S) & Real-Time Voice Agents

• Architect low-latency S2S pipelines that enable full-duplex conversational AI without the ASR/NLU/TTS handoff penalty.
• Partner with the Agentforce Reasoning team to integrate voice understanding with agent action loops (tool calls, CRM lookups, escalation routing).
• Establish interruption, barge-in, and turn-taking models appropriate for enterprise voice agents.

Speaker Diarization & Voice Analytics

• Deliver production speaker diarization ("who spoke when") for multi-party calls, enabling accurate per-speaker transcripts used in call coaching, compliance, and analytics.
• Develop speaker verification and voice-biometric capabilities for secure agent authentication use cases.
• Partner with the Einstein Analytics team to surface voice-derived signals (sentiment, engagement, talk-time ratios) in Salesforce dashboards.

Language Coverage & Localization

• Own the global language support roadmap; prioritize languages by customer demand, addressable market, and data availability.
• Establish data governance, annotation, and quality-control pipelines for low-resource languages.
• Work with regional Salesforce teams to validate dialect, accent, and cultural appropriateness of voice personas.

Engineering Leadership & Team Building

• Recruit, develop, and retain a world-class team of research engineers, applied scientists, and ML engineers (target team size: 20-30).
• Set technical direction, drive architectural decisions, and maintain engineering excellence through code review culture, rigorous evaluation frameworks, and production incident reviews.
• Build a culture of experimentation: rapid A/B testing, red-teaming for voice safety, and continuous model refreshes.

Cross-Functional Partnership

• Partner with Product Management to translate customer and regulatory requirements into model specifications and acceptance criteria.
• Collaborate with Legal, Privacy, and Trust & Safety on voice AI ethics, speaker consent, deepfake-detection, and compliance (HIPAA, PCI, GDPR).
• Represent Agentforce Voice at external conferences, standards bodies (W3C, IETF), and customer briefings.

Who You Are

Required Experience & Skills

• 10+ years in speech/audio machine learning, with 4+ years in a senior leadership role managing teams of 10 or more engineers or scientists.
• Deep hands-on expertise in at least two of: ASR (end-to-end or hybrid CTC/attention architectures), neural TTS (VITS, Voicebox, Matcha-TTS, or equivalent), or real-time speech processing pipelines.
• Proven track record of shipping production voice models at scale (millions of minutes per day) with measurable accuracy and latency improvements.
• Fluency in prosody modeling: pitch contour modeling, duration prediction, and expressiveness fine-tuning.
• Experience with speaker diarization systems (clustering-based, end-to-end, or hybrid).
• Strong understanding of multilingual and multi-dialect NLP/ASR challenges; experience with at least 5 languages in production.
• Proficiency in Python; experience with PyTorch or JAX model training at scale; familiarity with cloud-based training infrastructure (AWS, GCP, or Azure).
• Excellent written and verbal communication-able to translate complex model behavior into product and business narratives for executives.

Preferred Qualifications

• PhD in Computer Science, Electrical Engineering, Linguistics, or related field with a speech/audio focus, or equivalent industry experience.
• Familiarity with streaming inference, model quantization (INT8/INT4), and on-device deployment for low-latency voice.
• Experience with voice safety, watermarking, and deepfake/spoofing detection.
• Background in telephony protocols (SIP, RTP, WebRTC) and enterprise contact-center platforms (Genesys, NICE, Avaya, Amazon Connect).
• Published research or patents in speech processing, audio ML, or a closely related field.
• Experience operating within regulated industries (financial services, healthcare) with voice data compliance requirements.

Why Salesforce & Agentforce

• Work at the intersection of frontier research and enterprise-grade reliability, with direct customer impact across 150,000+ organizations worldwide.
• Have access to proprietary, enterprise-grade voice data, world-class compute, and a platform with distribution that no startup can match.
• Operate with the autonomy of a startup within the resources of a $35B+ company.
• Be part of Salesforce’s commitment to Responsible AI: building technology that is accurate, fair, transparent, and safe for every voice we serve.

Unleash Your Potential

When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love.

Accommodations

If you need a reasonable accommodation during the application or the recruiting process, please submit a request via this Accommodations Request Form.

Posting Statement

Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications - without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.

In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. More details about company benefits can be found at the following link: https://www.salesforcebenefits.com.Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records. At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions. The typical base salary range for this position is $197,300 - $313,700 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $237,700 - $344,700 annually. The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.