Motion Recruitment
Machine Learning Engineer / Voice-centric AI
Motion Recruitment, Chicago, Illinois, United States, 60290
Machine Learning Engineer / Voice-centric AI We’re looking for an entrepreneurial
Senior Machine Learning Engineer
with experience taking voice-centric AI systems (TTS, STT, LLM-driven dialog) from prototype to large-scale production. You’ll own the full ML lifecycle—research, data pipelines, training, evaluation, deployment, and ongoing optimization—powering sub-second, natural voice conversations at scale.
Do not pass up this chance, apply quickly if your experience and skills match what is in the following description. This role is ideal for someone passionate about
pushing the limits of conversational AI : creating highly optimized, domain-specific models that are faster, leaner, and more cost-efficient than general-purpose solutions. You’ll collaborate closely with product, infrastructure, and compliance teams, while setting the technical bar for model excellence and ML best practices. Required Skills & Experience Experience: 7+ years building production ML systems, including 2+ years in speech or conversational AI. Proven track record deploying large-scale voice AI or LLM products. Fine-tuning & compression (LoRA, QLoRA, quantization, pruning, distillation). Speech (ASR: Whisper, NeMo, Kaldi; TTS: Tacotron, FastSpeech, VITS). LLMs & dialogue (GPT-class, RAG, LangGraph, LangChain, MCP). Strong in Python; bonus for TypeScript/Node/Java. Infra & Ops (Kubernetes, Helm, Terraform, MLflow/SageMaker). Data systems (Kafka, Redis, Postgres, Snowflake). Streaming protocols (gRPC, WebSockets, HTTP/2, WebRTC). Security & compliance (HIPAA, SOC2, HITRUST). Product-oriented, entrepreneurial, strong problem solver, effective communicator, and technical leader. Desired Skills & Experience Optimize & Fine-Tune Models: Apply LoRA, QLoRA, RLHF, and other parameter-efficient techniques. Use quantization, pruning, and distillation to shrink models while preserving quality. Build End-to-End Pipelines: Design STT, TTS, and LLM systems achieving
Senior Machine Learning Engineer
with experience taking voice-centric AI systems (TTS, STT, LLM-driven dialog) from prototype to large-scale production. You’ll own the full ML lifecycle—research, data pipelines, training, evaluation, deployment, and ongoing optimization—powering sub-second, natural voice conversations at scale.
Do not pass up this chance, apply quickly if your experience and skills match what is in the following description. This role is ideal for someone passionate about
pushing the limits of conversational AI : creating highly optimized, domain-specific models that are faster, leaner, and more cost-efficient than general-purpose solutions. You’ll collaborate closely with product, infrastructure, and compliance teams, while setting the technical bar for model excellence and ML best practices. Required Skills & Experience Experience: 7+ years building production ML systems, including 2+ years in speech or conversational AI. Proven track record deploying large-scale voice AI or LLM products. Fine-tuning & compression (LoRA, QLoRA, quantization, pruning, distillation). Speech (ASR: Whisper, NeMo, Kaldi; TTS: Tacotron, FastSpeech, VITS). LLMs & dialogue (GPT-class, RAG, LangGraph, LangChain, MCP). Strong in Python; bonus for TypeScript/Node/Java. Infra & Ops (Kubernetes, Helm, Terraform, MLflow/SageMaker). Data systems (Kafka, Redis, Postgres, Snowflake). Streaming protocols (gRPC, WebSockets, HTTP/2, WebRTC). Security & compliance (HIPAA, SOC2, HITRUST). Product-oriented, entrepreneurial, strong problem solver, effective communicator, and technical leader. Desired Skills & Experience Optimize & Fine-Tune Models: Apply LoRA, QLoRA, RLHF, and other parameter-efficient techniques. Use quantization, pruning, and distillation to shrink models while preserving quality. Build End-to-End Pipelines: Design STT, TTS, and LLM systems achieving