Machine Learning Engineer

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