Cloud Engineer Machine Learning Ops

2 days ago

Durham NC United States Mastech Inc. Full time

Mastech Digital is an IT Staffing and Digital Transformation Services company.

Mastech Digital provides digital and mainstream technology staff as well as Digital Transformation Services for all American Corporations. We are currently seeking a Cloud Engineer Machine Learning Ops for our client in the Financial Services domain. We value our professionals, providing comprehensive benefits and the opportunity for growth. This is a Contract position, and the client is looking for someone to start immediately.

Duration: 12+ Months Contract

Location: Durham NC, Merrimack NH, Westlake TX

Primary Skills: Cloud Engineering

Role Description: The Cloud Engineer Machine Learning Ops must have at least 5+ years of experience. As a Cloud Engineer, you will build and maintain large scale ML Infrastructure and ML pipelines.

This role is a critical element to using the power of Data Science in delivering the client’s promise of creating the best customer experiences in financial services.

Responsibilities:

  1. Contribute to building advanced analytics, machine learning platforms and tools to enable both prediction and optimization of models.
  2. Extend existing ML Platform and frameworks for scaling model training and deployment.
  3. Partner closely with various business and engineering teams to drive the adoption and integration of model outputs.

The Expertise You Have:

  1. Bachelor’s or Master’s degree in a Technology related field (e.g., Engineering, Computer Science, etc.).
  2. Experience in Object Oriented Programming (Java, Scala, Python), SQL, Unix scripting or related programming languages and exposure to some of Python’s ML ecosystem (numpy, panda, sklearn, tensorflow, etc.).
  3. Experience in building cloud native applications using AWS services like S3, RDS, CFT, SNS, SQS, Step functions, Event Bridge, cloud watch etc.
  4. Experience with building data pipelines in getting the data required to build, deploy, and evaluate ML models, using tools like Apache Spark, AWS Glue or other distributed data processing frameworks.
  5. Data movement technologies (ETL/ELT), Messaging/Streaming Technologies (AWS SQS, Kinesis/Kafka), Relational and NoSQL databases (DynamoDB, EKS, Graph database), API and in-memory technologies.
  6. Strong knowledge of developing highly scalable distributed systems using Open-source technologies.
  7. 5+ years of proven experience in implementing Big data solutions in data analytics space.
  8. Experience in developing ML infrastructure and MLOps in the Cloud using AWS SageMaker.
  9. Extensive experience working with machine learning models with respect to deployment, inference, tuning, and measurement required.
  10. Experience with CI/CD tools (e.g., Jenkins or equivalent), version control (Git), orchestration/DAGs tools (AWS Step Functions, Airflow, Luigi, Kubeflow, or equivalent).
  11. Solid experience in Agile methodologies (Kanban and SCRUM).

Must Have Skills:

  1. Will be deploying ML Models via AWS SageMaker.
  2. SageMaker is an absolute must plus CI/CD experience.

Education: Bachelor’s degree in Computer Science, Electrical/Electronic Engineering, Information Technology or another related field or Equivalent

Experience: Minimum 5+ years of experience

Relocation: This position will not cover relocation expenses

Travel: No

Local Preferred: Yes

Note: Must be able to work on a W2 basis (No C2C)

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