Software Engineer - III

About the position

VIZIO's Technology - Software and Services team is seeking a talented and passionate Data Engineer AI/ML with mid-level career experience to join our dynamic team. This role is ideal for an engineer who has hands-on experience working with cutting-edge data solutions, generative AI, transformers, large language models (LLMs), RAGs, speech-to-text technologies, ASR, database optimization and localization algorithms. As a Data Engineer, you will contribute to developing and optimizing database solutions, employing innovative machine learning models and solutions that enhance our products and services. You will have the opportunity to work on impactful projects involving natural language processing (NLP), speech recognition, and AI-powered systems in a collaborative, fast-paced environment. This role will report to our Senior Manager of Software Engineering and this position will not have direct reports. We pride ourselves on being a collaborative team here at Vizio and to accomplish this, we are in the office 5 days a week in our Dallas, TX location.

Responsibilities

• Data Ownership: The role involves working with databases, data warehouses, queries, and scripts, and reporting information for end-users. This role will also own data engineering operations, troubleshooting data-related issues using SQL and other Integration monitoring tools, and maintain data-related documentation.
• Develop and Implement AI/ML Models: Design, develop, and optimize machine learning models for tasks such as text generation, language understanding, speech recognition, and localization. Focus on transformers and LLMs like GPT, BERT, and similar architectures.
• Generative AI Solutions: Build and deploy generative AI models, including text generation, conversational agents, and content creation tools that leverage state-of-the-art technologies.
• Hands-on in AI/ML: Fine tuning, creating AI workflows, integrating GenAI, expertise in cloud, AI/ML, modeling work, AI workflow integration within other applications, architecture experience a plus.
• Speech-to-Text Processing: Work on speech-to-text algorithms and systems to convert spoken language into accurate and actionable text data, using tools like deep learning models for ASR (Automatic Speech Recognition).
• Localization Algorithms: Implement and improve algorithms for the localization of text, speech, and other data to adapt to different languages, regions, and cultural nuances.
• Collaborate on Data Pipelines: Work closely with data engineers to build and optimize data pipelines for training AI models, ensuring high-quality, large-scale datasets are available for model development.
• Model Optimization & Deployment: Fine-tune models for better performance and efficiency in real-world environments. Assist in deploying AI models into production, ensuring scalability and reliability.
• NoSQL Systems: work on designing, normalizing, and structuring databases to meet application requirements while ensuring seamless integration with NoSQL systems and data lakes.
• Research & Innovation: Stay up to date with the latest advancements in AI/ML technologies, particularly in generative AI, transformers, and NLP, and integrate new techniques and algorithms into current workflows.
• Cross-Functional Collaboration: Work closely with other engineers, product managers, and stakeholders to ensure AI/ML solutions meet business needs and technical requirements.
• Tools: Implement and optimize AI/ML pipelines, leveraging AWS SageMaker, retrieval-augmented generation (RAG) techniques, and big data processing tools like Spark, Hive, and Airflow.

Requirements

• 3-5 years of professional experience in AI/ML engineering or data science with a focus on NLP, speech-to-text, and/or generative AI.
• Strong experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Hugging Face Transformers, Keras, or similar tools.
• Hands-on experience working with transformer models (e.g., BERT, GPT, T5) and large language models (LLMs) for a variety of NLP tasks (e.g., text generation, sentiment analysis, question answering).
• Experience in implementing and fine-tuning speech-to-text models or systems (e.g., using libraries such as Kaldi, DeepSpeech, or Google Speech-to-Text).
• Experience working with localization algorithms, tools, or libraries to adapt machine learning models for multiple languages and regions.
• Strong proficiency in Python and knowledge of libraries such as NumPy, pandas, scikit-learn, etc.
• Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and their AI/ML services for model training and deployment.
• Strong problem-solving skills with the ability to communicate complex technical concepts clearly and effectively to both technical and non-technical stakeholders.
• Ability to work in cross-functional teams, contributing to the development, deployment, and optimization of AI solutions.

Nice-to-haves

• Familiarity with transformer model fine-tuning for specific domains or tasks.
• Experience with speech recognition APIs and technologies (Google Speech API, Microsoft Azure Speech Services).
• SQL expertise to improve application integration with both SQL and No-SQL databases by query optimization, explain plan analysis, data indexing and modeling, and familiarity with monitoring data KPIs.
• Knowledge of multilingual NLP and techniques for handling non-English languages in NLP tasks.
• Expertise with Snowflake Cortex Large Language Model (LLM) functions and statistical modeling is a plus.
• Understanding of model explainability and ethical AI practices.
• Experience with model deployment using Docker, Kubernetes, or serverless.