What are the responsibilities and job description for the Senior Machine Learning Engineer Voice (Speech & NLP) position at GCS?
Job Details
Role Overview
The Applied AI Group within this Global Entertainment Engineering organization is seeking a Machine Learning Engineer with expertise in Natural Language Processing (NLP) to join a team of researchers and engineers. This team powers a voice platform used by millions worldwide, enabling customers to interact with their TVs through voice commands for searching content, controlling smart home devices, and retrieving entertainment-related information.
As part of the NLP team, you will design and build scalable, real-time data pipelines and feedback loops that enhance our models' accuracy and efficiency. You will work across the full ML development cycle, from prototyping to production deployment, ensuring robust and performant machine learning solutions. Your contributions will directly impact the stability, performance, and scalability of Comcast s voice and NLP-powered services.
Core Responsibilities
- Develop and maintain scalable, real-time data pipelines and feedback loops for training, tuning, and evaluating ML models serving production traffic.
- Design and optimize multi-lingual NLP models for voice query processing, including pattern matching, entity extraction, intent classification, and leveraging transformer models.
- Apply and fine-tune Generative AI models such as Phi, Qwen, Llama, and Gemma to enhance the capabilities of our voice platform.
- Build high-performance production systems capable of handling millions of daily requests, ensuring low-latency, real-time processing.
- Deploy and monitor machine learning models in a cloud environment (AWS), ensuring stability, reliability, and performance at scale.
- Collaborate with software engineers, product teams, and data scientists to define business objectives and implement production-ready AI solutions.
- Engage in architecture discussions, design reviews, and code reviews to ensure best practices in ML model deployment and software engineering.
- Continuously research and implement the latest advancements in LLMs, RAG (Retrieval-Augmented Generation) architecture, and prompt optimization.
Qualifications
- Bachelor s or Master s degree in Computer Science, Machine Learning, or a related field.
- 6 years of experience in machine learning, natural language processing (NLP), and deep learning.
- Proficiency in Python, Kotlin, and Java, with experience using ML frameworks such as TensorFlow, PyTorch, and Keras.
- Expertise in NLP techniques, including speech recognition, text classification, named entity recognition (NER), and transformer-based models.
- Hands-on experience with LLMs (large language models) and integrating them into real-time, low-latency data processing systems.
- Strong background in cloud computing (AWS), including deploying ML models using services like SageMaker, Lambda, API Gateway, and ECS.
- Experience with multi-lingual NLP systems and working with diverse linguistic datasets.
- Demonstrated ability to research, experiment, and implement innovative ML techniques in production settings.
- Strong communication skills to present complex technical concepts to both technical and non-technical stakeholders.
Preferred Qualifications
- Experience in edge AI and deploying NLP models to low-power devices.
- Hands-on experience with search ranking, recommendation systems, or conversational AI.
- Familiarity with MLOps best practices, CI/CD pipelines for ML, and monitoring ML models in production.
This role offers an exciting opportunity to be part of a dynamic team pushing the boundaries of voice-based AI, NLP, and Generative AI. If you re a passionate Machine Learning Engineer with a deep understanding of NLP, Generative AI, and cloud computing, we encourage you to apply and help us redefine how people interact with technology through voice.
