Machine Learning Engineer @ Viacom

Compensation

: $94,330.00 - $148,460.00 /year *

Employment Type

: Full-Time

Industry

: Manufacturing



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Responsibilities Build data pipelines for ML/NLP & other workloads. Build components to manage the machine learning lifecycle from feature engineering through deployment and monitoring. Build NLP pipeline using different open source libraries & products. Evaluate different NLP technology and tools. Gather and process raw data at scale (including writing scripts, web scraping, calling APIs, write SQL queries etc.). Develop sourcing, cleansing, structuring and ingesting new data sources. Write testable, readable code in Python (Java & Scala a plus) Analysis, creation & implementation of different data models & query languages, especially Graph also other db types Relational, Columnar, Document. Qualifications 5+ years of strong experience in Python. In-depth knowledge of Python data processing and machine learning libraries. Experience with data analysis, modeling. Strong knowledge in any or all of the following - Graph Databases, NoSql (MongoDb or CouchDb, Redis etc), relational databases (Postgres or Mysql), Apache solr or ElasticSearch. Experience with one or more of the following: Natural Language Processing, classification, topic modeling, pattern recognition, recommendation systems, ranking systems or similar. Experience with cloud based infrastructure, AWS or GCP. Preferred Qualifications: Experience with Deep learning & tooling like TensorFlow & PyTorch. Experience with Distributed execution platforms like Apache Spark or Apache Hadoop Experience with CI/CD. Education: Post Secondary Degree (BA, BSc, CS ) and or graduate (MA, MFA, MSc) B.S. in Computer Science or Engineering, M.S. preferred
Associated topics: data analyst, data analytic, data integration, data integrity, data manager, data management, data warehouse, data warehousing, database administrator, hbase * The salary listed in the header is an estimate based on salary data for similar jobs in the same area. Salary or compensation data found in the job description is accurate.

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