Data Scientist - REMOTE

Work Experience : 3 years

Industry : IT Services

Remote Job

Job Description

Data Scientist (MLOps)

Job Description:

We are seeking a versatile and adaptable Data Scientist with expertise in a range of

technology domains including Network Operations Infrastructure Management

Cloud Computing MLOpsDeep Learning NLP DevOps LLM infrastructure.

This role encompasses a wide range of responsibilities including designing and

implementing cloud solutions

building MLOps pipelines on cloud platforms (AWS Azure) orchestrating CI/CD

pipelines using tools like GitLab CI and GitHub Actions

and taking ownership of data pipeline and engineering infrastructure design to

support enterprise machine learning systems at scale.

Responsibilities:

Infra:

Manage cloudbased infrastructure on AWS and Azure focusing on scalability and

efficiency.

Utilize containerization technologies like Docker and Kubernetes for application

deployment.

NetOps

Monitor and maintain network infrastructure ensuring optimal performance and

security.

Implement loadbalancing solutions for efficient traffic distribution.

Infrastructure and Systems Management:

Cloud Computing:

Design and implement cloud solutions including the development of MLOps

pipelines.

Ensure proper provisioning resource management and cost optimization in a cloud

environment.

MLOps and DevOps:

Orchestrate CI/CD pipelines using GitLab CI and GitHub Actions for streamlined

software delivery.

Collaborate with data scientists and engineers to operationalize and optimize data

science models.

Apply software engineering rigor including CI/CD and automation to machine

learning projects.

Data Pipelines and Engineering Infrastructure:

Design and develop data pipelines and engineering infrastructure to support

enterprise machine learning systems.

Transform offline models created by data scientists into productionready systems.

Build scalable tools and services for machine learning training and inference.

Technology Evaluation and Integration:

Identify and evaluate new technologies to enhance the performance maintainability

and reliability of machine learning systems.

Develop custom integrations between cloudbased systems using APIs.

ProofofConcept Development:

Facilitate the development and deployment of proofofconcept machine learning

systems.

Emphasize auditability versioning and data security during development.

Requirements:

Strong software engineering skills in complex multilanguage systems.

Proficiency in Python and comfort with Linux administration.

Experience working with cloud computing and database systems.

Expertise in building custom integrations between cloudbased systems using APIs.

Experience with containerization (Docker) and Kubernetes in cloud computing

environments.

Familiarity with dataoriented workflow orchestration frameworks (KubeFlow

Airflow Argo etc.).

Ability to translate business needs into technical requirements.

Strong understanding of software testing benchmarking and continuous integration.

Exposure to machine learning methodology and best practices.

Exposure to deep learning approaches and modeling frameworks (PyTorch

TensorFlow Keras etc.).

If you are a dynamic engineer with a diverse skill set from cloud computing to

MLOps and beyond and you are eager to contribute to innovative projects in a

collaborative environment we encourage you to apply for this challenging and

multifaceted role. Join our team and help us drive technological excellence across

our organization.

Remote Work :

No