Machine Learning Engineer

Ovii's Interpretation of the Role

The Machine Learning Engineer will design and deploy speech and language models for multilingual Indian contexts, building real‑time conversational agents that handle interruptions and low‑latency requirements. The role blends research‑level ML work with production‑grade engineering and close collaboration with product, MLOps, and research teams.

Role Snapshot

• Design and optimize ASR/TTS models
• Develop real‑time conversational agents
• Build Agentic RAG and LLM pipelines
• Collaborate with MLOps for low‑latency deployment
• Partner with product and engineering teams

Must-Have Requirements

• Python
• PyTorch / TensorFlow / JAX
• ASR
• TTS
• NLP
• LLM fine‑tuning
• Low‑latency real‑time ML applications
• MLOps collaboration
• ML engineering
• speech/NLP systems
• Bachelor's degree in Computer Science, AI/ML, or related field

Nice-to-Have Signals

• Open‑source contributions
• Research publications
• Multilingual Indian‑context ASR/TTS experience
• open‑source contributions
• research publications

Work Setup

• Location: Bengaluru, India
• Work mode: ONSITE
• Employment type: Full-Time

Not Specified in JD

• Visa sponsorship
• Salary range
• Remote eligibility
• Relocation
• Notice period
• Travel
• Security clearance
• Coding test
• Portfolio
• GitHub
• Writing sample
• Cover letter

What You'll Likely Work On

• Design, train, and fine‑tune custom ASR/TTS models for Indian multilingual settings
• Build voice‑to‑voice systems using state‑space models
• Create agentic retrieval‑augmented generation pipelines and orchestrate LLMs for context‑aware voice agents
• Develop self‑learning agents that improve from human workflow feedback
• Deploy models with MLOps to achieve real‑time, low‑latency production performance
• Ensure scalability, security, and reliability of ML services
• Collaborate across product, engineering, and research to ship production‑ready features
• Stay current with advances in ASR, TTS, NLP, LLMs, and real‑time inference frameworks

Good Fit If You Have

• Passion for speech, LLM, and agentic AI research
• Experience delivering low‑latency ML systems at scale
• Track record of open‑source contributions or research publications