Senior Machine Learning Engineer
NICE
23 days ago
Atlanta, GA, USA
Senior
Responsibilities
- Conduct cutting-edge research and develop advanced speech recognition algorithms and models.
- Build and fine-tune deep learning and machine learning models, focusing on large language models.
- Work closely with internal stakeholders to define model requirements and ensure alignment with business objectives.
- Develop AI predictive models and perform data and model accuracy analyses.
- Produce and present findings, technical concepts, and model recommendations to both technical and non-technical stakeholders.
- Develop and maintain scripts/tools to automate both new model production and updates to existing model packages.
- Stay abreast of the latest advancements in data science research and contribute to the development of our knowledge base.
- Collaborate with developers to design automation and tool improvements for model building.
- Maintain documentation of processes and projects across all supported languages and environments.
Requirements
- Experience designing the internals of successful commercial speech recognition systems from vendors such as Microsoft, DeepGram, Meta, AssemblyAI, OpenAI, etc.
- Minimum of 5 years of machine learning work experience with at least 3 years working with deep learning models using real-life data.
- Advanced degree(s) in a STEM field such as Computer Science, Mathematics, Engineering, or equivalent practical experience.
- Excellent proficiency in Python programming and familiarity with deep learning libraries (e.g., PyTorch, TensorFlow).
- Experience turning inference from research level to enterprise production level.
- Advanced knowledge of statistical techniques and concepts (e.g., regression, statistical tests).
- Experience with building and/or fine-tuning large language models and traditional machine learning models.
- Strong research skills with a proven track record of developing and implementing NLP algorithms.
- Excellent verbal and written communication skills, including the ability to present complex concepts to technical and non-technical stakeholders.
- Experience with relational databases and query languages (e.g., SQL).
- Familiarity with version control (e.g., Git) and project management tools (e.g., Jira, Confluence).
Tech Stack
AWSGitPythonPyTorchSQLTensorFlow
Categories
AI & MLData Science