Machine Learning Software Engineer sought by Resonate Networks Inc. to design & develop robust data ingestion & processing pipelines using Apache Spark, Scala, Python & AWS cloud services. Oversee production, quality assurance & maintenance of data systems, ensuring efficient data flow & reliability. Collaborate with product management & data teams to implement Machine Learning feature pipelines for model training & scoring, leveraging Amazon SageMaker & TensorFlow where applicable. Analyze large datasets to derive insights that enhance feature development & optimize machine learning models.
REQ: Master's degree in Business Analytics, Info Systems, Comp Sci or closely related technical field & 1 yr exp in software engineering or Bachelor's degree in Business Analytics, Info Systems, Comp Sci or closely related technical field & 5 yrs' exp in software engineering. Exp must include 1 yr in each of the following: Amazon EMR for ETL pipelines; Scala/Spark for large scale data transformation (ETL); Linux based systems, Docker & code versioning tooling (Git, CI/CD); Python; Pandas; Numpy; PyTest & machine learning frameworks & data & computation management mechanisms that surround them in cloud environment (AWS).
Reston, VA. To apply go to https://job-boards.greenhouse.io/resonate, click on Machine Learning Software Engineer and click "Apply."
JOBS.NOW Note: To tap into these hidden job opportunities, it's crucial to adhere strictly to the application process outlined in each job ad. At JOBS.NOW, we ensure that every listing includes detailed employer instructions. Follow them precisely to be considered for these unique positions!
The Log Application button simply allows you to log the application for your records - JOBS.NOW does not submit any applications to employers directly. Remember to still apply through the method indicated in the job ad (mail, email, or via link).
Please note that JOBS.NOW is an independent website and does not post this listings on behalf of any employers nor do we receive any compensation for these listings. All listings are sourced via media or internet channels required by the PERM process.
