Cloud Engineer Machine Learning Ops - Mastech Digital

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

Role: Cloud Engineer Machine Learning Ops

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:

- Contribute to building advanced analytics, machine learning platforms and tools to enable both prediction and optimization of models. 

- Extend existing ML Platform and frameworks for scaling model training and deployment. 

- Partner closely with various business and engineering teams to drive the adoption and integration of model outputs. 

The Expertise You Have:

- Bachelor’s or Master’s degree in a Technology related field (e.g., Engineering, Computer Science, etc.).

- 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.).

- Experience in building cloud native applications using AWS services like S3, RDS, CFT, SNS, SQS, Step functions, Event Bridge, cloud watch etc.,

- 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.

- 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.

- Strong knowledge of developing highly scalable distributed systems using Open-source technologies.

- 5+ years of proven experience in implementing Big data solutions in data analytics space.

- Experience in developing ML infrastructure and MLOps in the Cloud using AWS SageMaker.

- Extensive experience working with machine learning models with respect to deployment, inference, tuning, and measurement required.

- Experience with CI/CD tools (e.g., Jenkins or equivalent), version control (Git), orchestration/DAGs tools (AWS Step Functions, Airflow, Luigi, Kubeflow, or equivalent).

- Solid experience in Agile methodologies (Kanban and SCRUM).

Must Have Skills:

- Will be deploying ML Models via AWS SageMaker. 

- AWS (SageMaker, Lambdas S3 Buckets)/ ETL/ Python/ Machine Learning Ops experience. 

- 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)

Recruiter Name: Vidushi Thakur

Recruiter Phone: 412-379-8945

Equal Employment Opportunity 

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