Machine Learning Engineer | Speech AI & NLP

Job Title\nMachine Learning Engineer | Speech AI & NLP\nLocation\nRemote / Hybrid\nExperience\n0–4 Years\nEmployment Type\nFull-Time\nAbout Company\nAn 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 at scale.\nRole Overview\nWe 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.\nYou will develop and deploy ML models that assess pronunciation, fluency, comprehension, grammar, vocabulary, and overall communication effectiveness.\nKey Responsibilities\nDesign, train, and deploy ML models for communication and language assessment.\nBuild speech-to-text and language understanding pipelines.\nDevelop automated scoring systems for spoken and written communication.\nWork with NLP, Speech Recognition, and Large Language Models (LLMs).\nBuild scalable ML services and APIs using Python.\nMonitor and improve model performance in production environments.\nRequired Qualifications\n0–4 years of experience in Machine Learning, NLP, Speech AI, or Applied AI.\nStrong proficiency in Python.\nExperience with PyTorch, TensorFlow, or similar ML frameworks.\nKnowledge of NLP frameworks such as Hugging Face, spaCy, or NLTK.\nUnderstanding of model training, evaluation, and deployment.\nStrong analytical and problem-solving skills.\nGood to Have\nExperience with Whisper, Wav2Vec2, Kaldi, DeepSpeech, or similar speech technologies.\nExperience with LLMs and Generative AI applications.\nFamiliarity with FastAPI, Docker, and cloud platforms (AWS/GCP/Azure).\nExposure to MLOps and production ML systems.\nUnderstanding of language assessment, educational testing, or communication evaluation platforms.