We are seeking a talented and experienced AI/ML Engineer with domain-specific
knowledge in multilingual audio signal and text processing, coupled with expertise in
data engineering and data processing pipelines. The ideal candidate will have a
strong background in artificial intelligence (AI) and machine learning (ML), with a
focus on audio signal processing, natural language processing (NLP), and
multilingual applications. This role requires proficiency in designing and
implementing robust data pipelines to handle large-scale multilingual datasets
effectively.
Responsibilities:
- Design and develop AI/ML algorithms and models for multilingual audio signal and text processing tasks, including speech recognition, language identification, translation, sentiment analysis, and text-to-speech synthesis.
- Implement advanced signal processing techniques for noise reduction, feature extraction, speaker diarization, and other audio preprocessing tasks to enhance the quality of audio data.
- Develop NLP models and techniques for text preprocessing, tokenization, language detection, named entity recognition, and semantic analysis across multiple languages.
- Design and implement scalable data engineering and processing pipelines to ingest, preprocess, and transform large-scale multilingual datasets for AI/ML model training and evaluation.
- Collaborate with cross-functional teams, including data scientists, software engineers, and domain experts, to define project requirements, data schemas, and performance metrics for AI/ML models.
- Optimize data pipelines for efficiency, scalability, and reliability, leveraging parallel processing, distributed computing, and cloud-based technologies as necessary.
- Conduct exploratory data analysis (EDA) and feature engineering to extract relevant insights and patterns from multilingual audio and text data.
- Evaluate and benchmark AI/ML models using appropriate metrics and evaluation methodologies, iterating on model design and hyperparameters to improve performance.
- Document research findings, experimental results, and software development processes to contribute to project documentation and knowledge sharing within the team.
- Stay updated with the latest advancements in AI/ML, signal processing, NLP, and data engineering through self-study, literature review, and participation in conferences and workshops.
Requirements:
- Bachelor's or Master's degree in Computer Science, Electrical Engineering,
- Linguistics, or a related field with a focus on AI/ML, signal processing, or NLP.
- 4+ years of industry experience in AI/ML engineering, with a proven track record of designing and deploying AI/ML solutions in real-world applications.
- Expertise in multilingual audio signal processing techniques, including noise reduction, feature extraction, speaker diarization, and audio preprocessing.
- Strong proficiency in NLP techniques and algorithms for text preprocessing, tokenization, language detection, named entity recognition, and semantic analysis.
- Experience in designing and building scalable data engineering and processing pipelines using tools and frameworks such as Apache Spark, Apache Beam, TensorFlow Extended (TFX), or similar.
- Proficiency in programming languages such as Python FastAPI and experience with relevant libraries and frameworks for AI/ML development (e.g., TensorFlow, PyTorch, scikit-learn).
- Solid understanding of distributed computing principles and experience with cloud-based platforms such as AWS, Azure, or Google Cloud Platform (GCP).
- Strong analytical and problem-solving skills, with the ability to analyze complex multilingual audio and text datasets and derive actionable insights.
- Excellent communication skills and the ability to collaborate effectively withcross-functional teams to drive project success.
- A passion for innovation and a drive to push the boundaries of AI/ML technology in multilingual audio and text processing applications.
