Machine Learning Engineer

Role: Machine Learning Engineer

Location: Atlanta, GA

Onsite role

USC/GC's are Encouraged for this position

***Candidates with the skill set listed but maybe with fewer years of experience is also fine, but has to be genuine.

Must Have Skills (Most Important)

Candidates must possess 8+ 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

Skills :