What are the responsibilities and job description for the Machine Learning Engineer - Voice (Speech & NLP) Group, Applied AI -- Machine Learning Engineer II (Contractor) position at ATR International, Inc.?
Job Details
Job Description:
We are seeking a Machine Learning Engineer - Voice (Speech & NLP) for a very important client
The Company brings together the best in media and technology We drive innovation to create the world's best entertainment and online experiences As a Fortune 50 leader, we set the pace in a variety of innovative and fascinating businesses and create career opportunities across a wide range of locations and disciplines We are at the forefront of change and move at an amazing pace, thanks to our remarkable people, who bring innovative products and services to life for millions of customers every day If you share in our passion for teamwork, our vision to revolutionize industries and our goal to lead the future in media and technology, we want you to fast-forward your career at the Company
Role Description
The Applied AI group in the Client's Global Entertainment Engineering organization is seeking a passionate and skilled Machine Learning Engineer with expertise in Natural Language Processing (NLP) to join a team of researchers and engineers powering a voice platform used by millions of people every day across the world We create the technology that powers the voice remote and allows our customers to interact with their TV to do things like search for content, control connected devices or find entertainment-related information
As a member of the NLP team, you will focus on building scalable, real-time data pipelines and feedback loops that help us train, tune and evaluate the models serving production traffic as well as the architecture that supports this We own the full process for taking an idea from a prototype to production You will collaborate with the team to identify the best solution to a problem, implement it, deploy it, and continuously monitor its performance The ideal candidate has a foundation in software development, experience building high performance production systems, and a robust background in machine learning particularly in multi-lingual NLP and current Generative AI techniques.
Core Responsibilities
Work as part of a team of software engineers in conjunction with product stakeholders to understand business objectives, define technical requirements and build features for production.
Apply NLP and ML knowledge to analyze and process voice queries using techniques like pattern matching, entity extraction, intent classification, and transformer models.
Support the application and fine-tuning of Generative AI models like Phi, Qwen, Llama, and Gemma to further our platform capabilities.
Contribute to building a scalable architecture that handles millions of requests per day.
Ensure the stability of our platform to serve our customers and assist with the deployment, monitoring, and troubleshooting of production systems.
Collaborate with teammates and contribute to design discussions, project planning and code reviews.
Demonstrate a keen sense of responsibility and accountability towards the team's work, its quality and timely delivery.
Requirement:
Qualifications
Bachelor's or Master's degree in Computer Science, Machine Learning or a related field.
2 years of relevant work or internship experience
Proficiency in programming languages like Python, Kotlin and Java and experience with machine learning frameworks such as TensorFlow, PyTorch and Keras
Experience with natural language processing, machine learning, deep learning, optimization techniques and evaluation methodologies
Experience with or exposure to LLMs and integrating them with complex real-time data processing and low-latency systems including methods for optimizing LLM prompts and using a RAG architecture
Experience with or exposure to cloud platforms (AWS) for deploying and managing ML models and its supporting architecture.
Experience with handling multi-lingual data and building systems that support multiple languages
Experience researching new ideas, formulating creative solutions and presenting sophisticated ideas to technical and non-technical audiences.
We are seeking a Machine Learning Engineer - Voice (Speech & NLP) for a very important client
The Company brings together the best in media and technology We drive innovation to create the world's best entertainment and online experiences As a Fortune 50 leader, we set the pace in a variety of innovative and fascinating businesses and create career opportunities across a wide range of locations and disciplines We are at the forefront of change and move at an amazing pace, thanks to our remarkable people, who bring innovative products and services to life for millions of customers every day If you share in our passion for teamwork, our vision to revolutionize industries and our goal to lead the future in media and technology, we want you to fast-forward your career at the Company
Role Description
The Applied AI group in the Client's Global Entertainment Engineering organization is seeking a passionate and skilled Machine Learning Engineer with expertise in Natural Language Processing (NLP) to join a team of researchers and engineers powering a voice platform used by millions of people every day across the world We create the technology that powers the voice remote and allows our customers to interact with their TV to do things like search for content, control connected devices or find entertainment-related information
As a member of the NLP team, you will focus on building scalable, real-time data pipelines and feedback loops that help us train, tune and evaluate the models serving production traffic as well as the architecture that supports this We own the full process for taking an idea from a prototype to production You will collaborate with the team to identify the best solution to a problem, implement it, deploy it, and continuously monitor its performance The ideal candidate has a foundation in software development, experience building high performance production systems, and a robust background in machine learning particularly in multi-lingual NLP and current Generative AI techniques.
Core Responsibilities
Work as part of a team of software engineers in conjunction with product stakeholders to understand business objectives, define technical requirements and build features for production.
Apply NLP and ML knowledge to analyze and process voice queries using techniques like pattern matching, entity extraction, intent classification, and transformer models.
Support the application and fine-tuning of Generative AI models like Phi, Qwen, Llama, and Gemma to further our platform capabilities.
Contribute to building a scalable architecture that handles millions of requests per day.
Ensure the stability of our platform to serve our customers and assist with the deployment, monitoring, and troubleshooting of production systems.
Collaborate with teammates and contribute to design discussions, project planning and code reviews.
Demonstrate a keen sense of responsibility and accountability towards the team's work, its quality and timely delivery.
Requirement:
Qualifications
Bachelor's or Master's degree in Computer Science, Machine Learning or a related field.
2 years of relevant work or internship experience
Proficiency in programming languages like Python, Kotlin and Java and experience with machine learning frameworks such as TensorFlow, PyTorch and Keras
Experience with natural language processing, machine learning, deep learning, optimization techniques and evaluation methodologies
Experience with or exposure to LLMs and integrating them with complex real-time data processing and low-latency systems including methods for optimizing LLM prompts and using a RAG architecture
Experience with or exposure to cloud platforms (AWS) for deploying and managing ML models and its supporting architecture.
Experience with handling multi-lingual data and building systems that support multiple languages
Experience researching new ideas, formulating creative solutions and presenting sophisticated ideas to technical and non-technical audiences.
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