Home › Companies › Sanas.AI Inc › Principal ML Engineer
Principal ML Engineer
Sanas.AI Inc · Palo Alto, CA, United States · On Site · Active · $250,000–$350,000 / year · Rippling ATS
Job facts
| Field | Value |
|---|---|
| Company | Sanas.AI Inc |
| Title | Principal ML Engineer |
| Normalized title | - |
| Department / team | Science |
| Location | Palo Alto, CA, United States |
| Work model | On Site |
| Employment type | Full Time |
| Salary | $250,000–$350,000 / year |
| Status | active |
| ATS provider | Rippling ATS |
| Posted / first seen | 2025-10-15 / 2026-06-06 |
| Changed / last seen | 2026-06-06 / 2026-06-06 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Sanas.AI Inc. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Rippling ATS. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| City jobs | Active postings in Palo Alto. | Open |
| Department jobs | Active postings in Science. | Open |
| Work model jobs | Active On Site postings. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Sanas.AI Inc |
| Source | 1fc1335f-581e-4138-ae2e-6e3d6c790876 |
| ATS provider | Rippling ATS |
Description
company
Sanas is pioneering the future of human communication. Founded by a team of Stanford researchers and entrepreneurs with deep industry experience, Sanas has developed the world's first real-time speech AI platform capable of accent translation, noise cancellation, speech enhancement, cross-language communication, and more.
Sanas makes conversations clearer, more inclusive, and more effective, removing barriers that prevent people from being understood, regardless of accent, background noise, or native language.
Sanas is currently one of the fastest growing startups in Silicon Valley, growing from $16M to $50M ARR in 2025. The company's core business is profitable and is on track to end 2026 with >$120M ARR. Our team combines deep expertise in model innovation and systems engineering with a design-minded product engineering culture to build and ship cutting-edge AI models and experiences — entirely in-house.
Sanas is a 180-strong team, established in 2020. In this short span, we've successfully secured over $100 million in funding. Our innovation has been supported by the industry's leading investors, including Insight Partners, Google Ventures, Quadrille Capital, General Catalyst, Quiet Capital, and other influential investors. Our reputation is further solidified by collaborations with numerous Fortune 100 companies. With Sanas, you're not just adopting a product; you're investing in the future of communication.
If you’re looking to have a significant role in roadmapping and driving technical directions, if you’re looking to deploy challenging and big ideas without much overhead or slowness, if you're looking to leave your mark on an ambitious, generational mission to change how the worlds thinks about speech + AI, then Sanas is a well-suited place for you.
role
About the role
Weʼre looking for an experienced and forward-thinking Principal Machine Learning Engineer to lead the design and implementation of our end-to-end Machine Learning infrastructure for industry leading Voice AI products. This is a high impact role where you will shape the technical vision, own strategic architecture decisions, and mentor a growing team of Machine Learning engineers focused on delivering reliable and scalable Machine Learning training and inference systems.
Youʼll work cross-functionally with AI research scientists, Infrastructure and product teams to ensure that Machine Learning infrastructure is designed and built for accelerating innovation through increased experimentation and deployment velocity. Youʼll help push the boundaries of real-time Voice AI
What you'll do
Architect robust, modular ML pipelines for model experimentation, feature extraction, and production inference Collaborate with data engineering to improve audio dataset quality, labeling pipelines, and feature engineering Mentor and collaborate with other ML engineers and research scientists to ensure best practices in model development, evaluation, and deployment. Optimize models for latency, memory, and real-time performance on CPU/GPU/edge hardware. Introduce frameworks for continual learning, model versioning, and A/B testing in production. Stay current with advancements in Voice AI, Deep learning and multimodal model architectures Qualifications
10+ years of experience in Machine Learning Systems, ML workflows with atleast 3+ years in a technical leadership capacity Advanced proficiency in Python and ML frameworks like PyTorch, TensorFlow, or JAX Strong understanding of Deep learning architectures like RNNs, LSTMs, CNNs,Transformers, CTC and their application in Accent translation, Noise cancellation, Acoustic Modeling, Language Modeling and Language Translation Experience deploying ML models to production (e.g., via ONNX, TensorRT, TorchScript, or custom inference stacks) Nice to Have:
Familiarity with audio data and its unique challenges, like large file sizes, time- series features, metadata handling, is a strong plus. Experience with Voice AI models like ASR, TTS and speaker verification. Familiarity with real-time data processing frameworks like Kafka, Flink, Druid and Pinot Familiarity with ML workflows including: MLOps, feature engineering, model training and inference. Experience with labeling tools, audio annotation platforms, or human-in-the- loop annotation pipelines. Experience at a high-growth startup or tech company operating at scale. Deep experience with ML tooling for training and serving models, ideally in audio or speech domains (e.g., PyTorch, ONNX, Hugging Face Transformers, torchaudio). Experience deploying real-time ASR, TTS, or voice synthesis models in production. Background in DSP, audio augmentation, or working with noisy or multilingual datasets.
Full job record
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| Provider Job Key | 422fb87f-02f6-45d8-8f2c-6202a235dae9 |
| Title | Principal ML Engineer |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | Palo Alto, CA, United States |
| Department | Science |
| Team | — |
| Employment Type | full_time |
| Workplace Type | on_site |
| Remote Policy | — |
| Country | United States |
| Region | CA |
| City | Palo Alto |
| Salary Raw | USD 250000-350000 YEAR |
| Salary Min | 250,000 |
| Salary Max | 350,000 |
| Salary Currency | USD |
| Salary Period | year |
| Source URL | https://ats.rippling.com/sanas/jobs/422fb87f-02f6-45d8-8f2c-6202a235dae9 |
| Apply URL | https://ats.rippling.com/sanas/jobs/422fb87f-02f6-45d8-8f2c-6202a235dae9 |
| First Seen At | 2026-06-06 08:42:22Z |
| Last Seen At | 2026-06-06 19:34:57Z |
| Last Checked At | 2026-06-06 19:34:57Z |
| Last Changed At | 2026-06-06 19:34:57Z |
| Inactive At | — |
| Source Posted At | 2025-10-15 06:56:47Z |
| Source Updated At | — |
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"role": "<meta><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:8pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><b><strong style=\"font-size:15pt;white-space:pre-wrap;\">About the role</strong></b></p><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;text-align:start;\"><span style=\"font-size:12pt;white-space:pre-wrap;\">Weʼre looking for an experienced and forward-thinking Principal Machine Learning Engineer to lead the design and implementation of our end-to-end Machine Learning infrastructure for industry leading Voice AI products. This is a high impact role where you will shape the technical vision, own strategic architecture decisions, and mentor a growing team of Machine Learning engineers focused on delivering reliable and scalable Machine Learning training and inference systems.</span></p><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br></p><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;text-align:start;\"><span style=\"font-size:12pt;white-space:pre-wrap;\">Youʼll work cross-functionally with AI research scientists, Infrastructure and product teams to ensure that Machine Learning infrastructure is designed and built for accelerating innovation through increased experimentation and deployment velocity. Youʼll help push the boundaries of real-time Voice AI</span></p><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><b><strong style=\"font-size:18pt;white-space:pre-wrap;\">What you'll do</strong></b></p><ul data-pattern=\"discCircleSquare\" data-depth=\"1\" style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;margin:8px 0px;line-height:1.6;padding:0px 0px 0px 32px;list-style-type:disc;\"><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Architect robust, modular ML pipelines for model experimentation, feature extraction, and production inference</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Collaborate with data engineering to improve audio dataset quality, labeling pipelines, and feature engineering</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Mentor and collaborate with other ML engineers and research scientists to ensure best practices in model development, evaluation, and deployment.</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Optimize models for latency, memory, and real-time performance on CPU/GPU/edge hardware.</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Introduce frameworks for continual learning, model versioning, and A/B testing in production.</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Stay current with advancements in Voice AI, Deep learning and multimodal model architectures</span></li></ul><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><b><strong style=\"font-size:18pt;white-space:pre-wrap;\">Qualifications</strong></b></p><ul data-pattern=\"discCircleSquare\" data-depth=\"1\" style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;margin:8px 0px;line-height:1.6;padding:0px 0px 0px 32px;list-style-type:disc;\"><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">10+ years of experience in Machine Learning Systems, ML workflows with atleast 3+ years in a technical leadership capacity</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Advanced proficiency in Python and ML frameworks like PyTorch, TensorFlow, or JAX</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Strong understanding of Deep learning architectures like RNNs, LSTMs, CNNs,Transformers, CTC and their application in Accent translation, Noise cancellation, Acoustic Modeling, Language Modeling and Language Translation</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Experience deploying ML models to production (e.g., via ONNX, TensorRT, TorchScript, or custom inference stacks)</span></li></ul><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:15pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><b><strong style=\"font-size:15pt;white-space:pre-wrap;\">Nice to Have: </strong></b></p><ul data-pattern=\"discCircleSquare\" data-depth=\"1\" style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;margin:8px 0px;line-height:1.6;padding:0px 0px 0px 32px;list-style-type:disc;\"><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Familiarity with audio data and its unique challenges, like large file sizes, time- series features, metadata handling, is a strong plus.</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Experience with Voice AI models like ASR, TTS and speaker verification.</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Familiarity with real-time data processing frameworks like Kafka, Flink, Druid and Pinot</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Familiarity with ML workflows including: MLOps, feature engineering, model training and inference.</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Experience with labeling tools, audio annotation platforms, or human-in-the- loop annotation pipelines.</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Experience at a high-growth startup or tech company operating at scale.</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Deep experience with ML tooling for training and serving models, ideally in audio or speech domains (e.g., PyTorch, ONNX, Hugging Face Transformers, torchaudio).</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Experience deploying real-time ASR, TTS, or voice synthesis models in production.</span></li><li style=\"font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Background in DSP, audio augmentation, or working with noisy or multilingual datasets.</span></li></ul>",
"company": "<meta><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;text-align:start;\"><span style=\"white-space:pre-wrap;\">Sanas is pioneering the future of human communication. Founded by a team of Stanford researchers and entrepreneurs with deep industry experience, Sanas has developed the world's first real-time speech AI platform capable of accent translation, noise cancellation, speech enhancement, cross-language communication, and more.</span><br><br><span style=\"white-space:pre-wrap;\">Sanas makes conversations clearer, more inclusive, and more effective, removing barriers that prevent people from being understood, regardless of accent, background noise, or native language.</span><br><br><span style=\"white-space:pre-wrap;\">Sanas is currently one of the fastest growing startups in Silicon Valley, growing from $16M to $50M ARR in 2025. The company's core business is profitable and is on track to end 2026 with >$120M ARR. Our team combines deep expertise in model innovation and systems engineering with a design-minded product engineering culture to build and ship cutting-edge AI models and experiences — entirely in-house.</span><br><br><span style=\"white-space:pre-wrap;\">Sanas is a 180-strong team, established in 2020. In this short span, we've successfully secured over $100 million in funding. Our innovation has been supported by the industry's leading investors, including Insight Partners, Google Ventures, Quadrille Capital, General Catalyst, Quiet Capital, and other influential investors. Our reputation is further solidified by collaborations with numerous Fortune 100 companies. With Sanas, you're not just adopting a product; you're investing in the future of communication.</span><br><br><span style=\"white-space:pre-wrap;\">If you’re looking to have a significant role in roadmapping and driving technical directions, if you’re looking to deploy challenging and big ideas without much overhead or slowness, if you're looking to leave your mark on an ambitious, generational mission to change how the worlds thinks about speech + AI, then Sanas is a well-suited place for you.</span></p>"
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}Get this page with API
Rendered from the bluedoor Job Postings API. Reproduce it:
GET https://api.bluedoor.sh/job-postings/v1/jobs/ddba754ff6c479b9b761b4db6b142052f0814732?include=descriptionJSONGET https://api.bluedoor.sh/job-postings/v1/orgs/83ad35d8-903f-4812-a8a1-7e0502248692JSONGET https://api.bluedoor.sh/job-postings/v1/sources/1fc1335f-581e-4138-ae2e-6e3d6c790876JSONGET https://api.bluedoor.sh/job-postings/v1/jobs/ddba754ff6c479b9b761b4db6b142052f0814732/eventsJSON