Lead / Staff ML Scientist - Speech

Who we are

We at Agara believe voice conversations should be without friction, without barriers, and without frustration. Pushing the boundaries of deep learning, we are building ubiquitous, pleasant, and meaningful machine-led voice conversations accessible to all. Agara’s AI voice agents talk to customers around the globe. Most of our work involves building conversational AI systems, using speech technology and natural language processing.

What you’ll do

Design, build and train robust deep learning speech systems that power Agara’s real-time conversations across languages, accents, noise environments, and voice interfaces. You will work closely with a team of machine learning scientists and engineers to train and produce speech models. Applied research and experimentation will be an integral part of your role. 

We require that you have

• B.Tech, M.Tech or Ph.D. in Computer Science or equivalent work experience


• Relevant work experience of 6+ years


• Enthusiastic to work in a fast-paced environment, along with machine learning scientists and engineers


• Comfortable with at least one deep learning framework (PyTorch / Tensorflow)


• Previous extensive experience building real-world speech systems such as speech recognition, text to speech, speaker diarization


• Passionate about innovation and pushing the state of art in speech


• Excellent programming skills in Python

Bonus if you have

• Publications in top-tier journals/conferences such as ICASSP, NeurIPS, PAMI, InterSpeech.


• Previous experience building voice conversational AI systems


• Experience working with textual NLP systems

What we offer

Apart from all the general benefits of best in industry compensation, benefits, and perks, we are proud of our great talent, great work, and great culture. We believe in mutual trust, flexibility, and transparency.

Halli Labs Private Limited (Agara) is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, ancestry, age, physical or mental disability, sex, sexual orientation, gender identity/expression, pregnancy, veteran status, marital status, creed, status with regard to public assistance, genetic status or any other status protected by federal, state or local law.