Senior ML Engineer
New
RemoteFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 4 years of professional experience in machine learning or data science
- Required Skills
- SQLAgileETLMachine LearningDatabricksNLPMLOpsPySpark
Requirements
- Bachelor’s degree in a STEM field.
- 4 years of professional experience in machine learning or data science, with a focus on production-grade deployments.
- Demonstrated experience with Databricks, PySpark, and SQL for large-scale data manipulation.
- Proven experience with MLOps practices, including model engineering, orchestration, and monitoring.
- Background in applied Natural Language Processing (NLP), including data labeling and entity/keyword extraction.
- Strong understanding of statistical distributions and their application in predictive data modeling.
- Excellent communication skills with the ability to present technical findings to diverse audiences and stakeholders.
- Proficiency with office productivity software, including Microsoft Excel, Word, and PowerPoint.
- Ability to travel, as needed, to engage with government customers and stakeholders.
Responsibilities
- Architect and maintain production-grade ML pipelines and infrastructure to support program-wide CBM+ initiatives.
- Oversee end-to-end data collection and processing, including the implementation and sustainment of robust ETL pipelines.
- Drive the adoption of MLOps practices to ensure automated model deployment, versioning, and rigorous monitoring.
- Partner closely with data scientists to transition models from experimental stages to production environments efficiently.
- Clean, preprocess, and manage large-scale datasets to ensure high-quality inputs for predictive modeling.
- Perform Exploratory Data Analysis (EDA) and statistical visualization to identify correlations and trends.
- Identify and implement opportunities to improve system performance, scalability, and computational efficiency.
- Continuously monitor deployed models for performance drift and degradation, implementing retraining strategies as needed.
- Collaborate within a multi-functional Agile team to align technical tasks with evolving mission objectives.
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