Machine Learning Engineer
2 months ago
Client Verizon - Rate 65
MLOP is mandatory
Machine Learning Engineer
Location: Alpharetta-GA-USA Hybrid (three days a week)
Duration 12 months
MUST HAVE SKILLS (Most Important):
• Candidates must possess 7+ years of overall software development experience.
• Must have 7+ years of relevant work experience in data ingestion on streaming / real-time platforms.
• Must have 7+ years of recent experience as a developer using Java/C++/Python
• Must have 7+ years of recent experience working with data stream processing technologies like DataFlow, IBM Streams, Apache Flink, or Spark Streaming
• Must have 7+ years' experience operationalizing AI/ML pipelines in a real-time environment
• Must have 7+ years' experience building input streaming data pipelines for AI/ML use cases
• Must have experience implementing NLP models in real-time environment
• Must have 7+ years of recent experience working with streaming data stores like Cassandra or Redis
• Must have experience of handling Large volume of data in terabytes as well low volume but high frequency data
• Must have 7+ years of recent experience working with messaging queue technologies like Pub/Sub, Kafka and Rabbit MQ
• Must have 7+ years' experience on Unix based OS
• Exposure to NoSQL-based, SQL-like technologies (e. g., Hive, Pig, Spark SQL/Shark, Impala, BigQuery, Cassandra).
• Exposure to Google Cloud Platform (GCP) and integrating it with real-time data streaming applications
• Some experience with container technologies like Kubernetes and Docker
DESIRED SKILLS:
• Ability to work independently, and multi-task under short deadlines, based upon general direction
• Telecom domain knowledge is preferred
• Able to mentor, guide and lead a team of streaming ML engineers
• Demonstrated effective verbal and written communication skills.
• Good Knowledge in Hadoop platform including Big Data tools
• Some experience with data warehousing and data lakes
JOB DUTIES:
• Primary responsibility is to design, develop, and implement MLOps for our NLP real-time models
• Another key responsibility will be to help implement data streaming pipelines for new data sources to feed to our NLP real-time models
• Help develop self-service applications in the real-time environment to help with various use cases
• Doing proof of concepts to expand current platform capabilities
• Closely collaborate with cross-functional teams
• The successful candidate will have an understanding of coding and a strong sense of architecture, deployment and operational skill.
• Expect to be on-site for most weekdays
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