Associate Machine Learning Engineer

JobgetherMachine learning

Fully remote working arrangement within the United StatesFull-TimeJunior

Salary106,900 - 152,700 USD per year

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Job Details

Experience: 0–2 years of experience in machine learning engineering, software engineering, data engineering, or a related technical field.
Required Skills: AWSPythonGCPMachine LearningMicrosoft AzureData engineeringSparkCI/CDDatabricks

Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, Machine Learning, or another related quantitative discipline.
0–2 years of experience in machine learning engineering, software engineering, data engineering, or a related technical field.
Experience using Python through academic projects, internships, research, or professional work.
Foundational understanding of machine learning concepts, algorithms, model development, and deployment processes.
Familiarity with version control, software testing, debugging, and code review practices.
Basic understanding of data engineering principles, data structures, and automated pipeline development.
Exposure to cloud computing platforms such as AWS, Microsoft Azure, or Google Cloud Platform is an advantage.
Strong analytical thinking and problem-solving abilities.
Ability to collaborate with technical and non-technical stakeholders.
Ability to manage assigned tasks independently while recognizing when senior guidance is needed.
A bachelor’s-level background in a related quantitative discipline is required.

Collaborate with machine learning engineers, data scientists, data engineers, DevOps specialists, and other technical teams to support machine learning solutions.
Build, test, maintain, and improve software components and infrastructure for machine learning applications.
Develop and maintain automated data pipelines, machine learning workflows, and model deployment processes.
Support cloud-based machine learning solutions using AWS, Databricks, and Apache Spark.
Participate in CI/CD processes to improve automation, deployment reliability, and operational efficiency.
Monitor machine learning applications, investigate technical issues, and work with senior engineers on solutions.
Help maintain scalable infrastructure and tooling for AI and machine learning capabilities.
Contribute to technical discussions, cross-functional meetings, and project planning.
Document technical solutions, development processes, and lessons learned.
Follow software engineering, machine learning, security, data governance, and development standards.

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