Applied Machine Learning, Voice

Company: NLP PEOPLE
Location: San Francisco
Posted on: May 20, 2025

Job Description:

Who is Recruiting from Scratch:Recruiting from Scratch is a talent firm that focuses on placing the best candidate for our clients.Applied Machine Learning Engineer - Audio AILocation: San Francisco, CA or New York, NY (Onsite strongly preferred)Company Stage of Funding: Seed/Series AOffice Type: Onsite 5 Days a WeekSalary: $200,000 - $250,000 + Competitive EquityCompany DescriptionOur client is a rapidly growing startup revolutionizing the world of audio AI. Their mission is to build best-in-class infrastructure and models for collecting and training on large-scale, high-fidelity speech and audio datasets across diverse languages and dialects. With a dataset that is already 10x larger than the next largest available, they are empowering leading AI labs and enterprises to push the boundaries of voice technology.This is an incredible opportunity to join a team of ambitious engineers and researchers with a proven track record in building scalable ML systems. You'll be working on cutting-edge technology in a space that is only beginning to boom-and you'll help shape its trajectory from the ground up.What You Will Do
--- Research, design, and implement advanced machine learning and signal processing solutions focused on speech and audio applications.
--- Build production-grade ML inference pipelines and APIs, collaborating closely with cross-functional teams.
--- Architect and maintain resilient systems for model inference, evaluation, and performance tracking.
--- Own ML initiatives from proof-of-concept to deployment, influencing both roadmap and architecture.
--- Work hand-in-hand with operations and data teams to gather training/evaluation data and enhance model quality.
--- Lead infrastructure and research efforts to ensure model accuracy, performance, and scalability.Ideal Candidate Background
--- 5+ years of hands-on experience in machine learning, with at least 2 years focused on audio/speech ML or DSP algorithm development.
--- Proven ownership of ML pipelines end-to-end, including production deployment and post-launch optimization.
--- Background includes at least 1 year of prior software development experience before transitioning into ML.
--- Experience with speech or audio research, particularly in applying ML models to real-world signal processing problems.
--- High-growth, high-performance trajectory at prior companies (e.g., promotions, leadership roles).
--- Strong academic background (e.g., top-tier university or research-focused program).Preferred Qualifications
--- Master's or PhD in Computer Science, Electrical Engineering, or related field with a focus on signal processing or ML.
--- Experience training generative AI or speech recognition models.
--- Expertise in classical signal processing techniques as well as modern ML approaches.
--- Familiarity with production systems involving cloud infrastructure (AWS, GCP).
--- Proficient in Python and frameworks like PyTorch.
--- Capable of translating research ideas into high-quality code and products.
--- Understands how to connect technical quality with end-user experience and product value.Compensation, Benefits, and Other Perks
--- Competitive base salary of $200K-$250K with generous equity package.
--- 401k plan access.
--- Comprehensive health, dental, and vision insurance-100% company-paid for most plans.
--- Flexible PTO policy.
--- Daily DoorDash credits for office lunch and dinner.
--- Opportunity for rapid career growth at a high-velocity startup.
--- Work alongside a talented, tight-knit, and humble team of ML and product builders.If you're excited about shaping the future of audio AI and want to make a real impact on speech-driven technologies, we want to hear from you.Company:Recruiting from ScratchQualifications:Language requirements:Specific requirements:Educational level:Level of experience (years):Senior (5+ years of experience)Tagged as: , , , ,
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Keywords: NLP PEOPLE, Santa Clara , Applied Machine Learning, Voice, Other , San Francisco, California