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Machine Learning Engineer | Speech AI & NLP

Job in 400001, Mumbai, Maharashtra, India
Listing for: DMAIC Academy & Consultancy
Full Time position
Listed on 2026-06-17
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software), Data Scientist
Job Description & How to Apply Below
Job Title
Machine Learning Engineer | Speech AI & NLP
Location
Remote / Hybrid
Experience
0–4 Years

Employment Type

Full-Time
About Company
An AI-driven HR Tech company building intelligent assessment and hiring solutions. We leverage Machine Learning, Speech AI, NLP, and Generative AI to evaluate communication skills and improve talent decision-making e Overview
We are looking for a Machine Learning Engineer with experience in Speech AI, NLP, and Applied AI to build systems that evaluate Listening, Speaking, Reading, and Writing (LSRW) skills.
You will develop and deploy ML models that assess pronunciation, fluency, comprehension, grammar, vocabulary, and overall communication effectiveness.

Key Responsibilities
Design, train, and deploy ML models for communication and language assessment.
Build speech-to-text and language understanding pipelines.
Develop automated scoring systems for spoken and written communication.
Work with NLP, Speech Recognition, and Large Language Models (LLMs).
Build scalable ML services and APIs using Python.
Monitor and improve model performance in production environments.

Required Qualifications
0–4 years of experience in Machine Learning, NLP, Speech AI, or Applied AI.
Strong proficiency in Python.

Experience with PyTorch, Tensor Flow, or similar ML frameworks.
Knowledge of NLP frameworks such as Hugging Face, spaCy, or NLTK.
Understanding of model training, evaluation, and deployment.
Strong analytical and problem-solving skills.
Good to Have

Experience with Whisper, Wav2

Vec2, Kaldi, Deep Speech, or similar speech technologies.

Experience with LLMs and Generative AI applications.
Familiarity with FastAPI, Docker, and cloud platforms (AWS/GCP/Azure).
Exposure to MLOps and production ML systems.
Understanding of language assessment, educational testing, or communication evaluation platforms.
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