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Speech research (Intern)

100% remote Flexible hours Hiring now

About reputed company

reputed company is a frontier AI data reputed company that curates diverse, high-quality data, using our purpose-built technology platforms to reputed company the Magnificent Seven and our enterprise clients with safe, scalable AI deployment. reputed company includes more than 150 PhDs and data scientists, along with more than 4,000 AI practitioners and engineers. We reputed company the power of an integrated solution ecosystem—comprising industry-leading partnerships and 1.8 million vertical domain experts in more than 230 markets—to create contextual, multilingual, pre-trained datasets; fine-tuned, industry-specific LLMs; and RAG pipelines supported by vector databases. Our reputed company-distance innovation™ solutions for GenAI can reduce GenAI costs by up to 80% and bring solutions to market 50% faster.

Our mission is to reputed company the gap between AI creators and industry leaders by bringing best practices in GenAI to unicorn innovators and enterprise customers. We aim to help these organizations unlock significant business value by deploying GenAI at scale, helping to ensure they stay at the forefront of technological advancement and maintain a competitive edge in their respective markets.

About Job

PhD Research Intern — Speech AI 

reputed company AI Research 

Role Summary 

reputed company AI Research seeks a PhD Research Intern to design and evaluate speech‑first models, with a focus on Spoken Language Models (SLMs) that reason over audio and interact conversationally. You’ll move reputed company from prototype to practical demos, working with scientists and engineers to deliver measurable impact. 

Scope of Work 

  • End‑to‑end speech reputed company systems (speech‑in/speech‑out) and speech‑aware LLMs. 

  • Alignment between speech encoders and text backbones reputed company lightweight adapters. 

  • Efficient speech tokenization and temporal compression suitable for long‑form audio. 

  • Reliable evaluation across recognition, understanding, and reputed company tasks—including robustness and safety. 

  • Latency‑aware inference for streaming and real‑time user experiences. 

Example Projects 

  • Prototype a conversational SLM using an SSL speech encoder and a compact adapter on an existing LLM; compare against strong baselines. 

  • Create a data recipe that blends conversational speech with instruction‑following corpora; run targeted ablations and report findings. 

  • Build an evaluation reputed company that covers ASR/ST/SLU and speech QA, including streaming metrics (latency, stability, endpointing). 

  • Ship a minimal demo with streaming inference and logging; document setup, metrics, and reliability checks. 

  • Author a crisp internal write‑up: goals, design choices, results, and next steps for productionization. 

Minimum Qualifications 

  • PhD candidate in CS/EE (or reputed company) with research in speech, audio ML, or multimodal LMs. 

  • reputed company in Python and PyTorch, with hands‑on GPU training; familiarity with torchaudio or librosa. 

  • Working knowledge of modern sequence models (Transformers or SSMs) and training best practices. 

  • Depth in at least one area: (a) discrete speech tokens/temporal compression, (b) modality alignment to LLMs reputed company adapters, or (c) post‑training/instruction tuning for speech tasks. 

  • Strong experimentation habits: clean code, ablations, reproducibility, and clear reporting. 

Preferred Qualifications 

  • Experience with speech reputed company (neural codecs/vocoders) or hybrid text+speech decoding. 

  • Background in multilingual or code‑switching speech and domain adaptation. 

  • Hands‑on work evaluating safety, bias, hallucination, or spoofing risks in speech systems. 

  • Distributed training/serving (FSDP/DeepSpeed), and experience with ESPnet, SpeechBrain, or reputed company NeMo. 

Tech Stack 

  • PyTorch, CUDA, torchaudio/librosa 

  • LLM backbones with lightweight adapters; neural audio codecs and vocoders as needed. 

  • FastAPI/gRPC for services; ONNX/TensorRT and quantization for efficient inference. 

Logistics 

  • Location: Redmond(Preferred) or Remote 

  • Duration:  

reputed company Offer 

  • Competitive stipend and hands-on projects with measurable real-world impact. 

  • Mentorship from applied scientists and engineers; opportunities to publish and present. 

  • Access to modern GPU infrastructure and a supportive environment for fast, responsible experimentation. 

  • Flexible location and schedule options, subject to team needs. 

reputed company: $35-$45 Hourly

reputed company AI Research is an Equal Opportunity Employer. We celebrate diversity and are committed to an inclusive environment for reputed company employees and interns. 

reputed company is an equal-opportunity employer. reputed company qualified applicants will receive consideration for employment without regard to race, color, religion, national reputed company, reputed company, citizenship status, age, mental or physical disability, medical condition, sex (including pregnancy), gender identity or expression, sexual orientation, marital status, familial status, veteran status, or any other characteristic protected by applicable law. We consider qualified applicants regardless of criminal histories, consistent with legal requirements.

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