TL;DR

Machine Learning Engineer II (Cybersecurity): Developing, enhancing, and maintaining machine learning pipelines and data science solutions, including data pipelines, infrastructure, and deployment of ML models with an accent on optimizing, testing, and evaluating ML models. Focus on exploring MLOps and data science topics and technologies, acquiring expertise on developing ML models including LLMs and generative models, and writing technical documentation.

Location: null

Salary: null

Company

%hirify_global% is breaking the attack chain.

What you will do

Work on various ML engineering projects with minimal supervision.
Collaborate with data scientists to optimize, test, and evaluate ML models.
Help to design, develop, document, test, and debug software engineering solutions for both customer-facing applications and internal use.
Help to deploy, scale, and maintain machine learning models in production environments.
Write technical documentation of small-scale components based on architectural design and stated engineering requirements.

Requirements

At least 4 years of experience in engineering and/or data science roles is required. At least one year of ML engineering experience is desirable.
Solid experience developing system architecture and solving engineering problems in at least one major programming language such as Python, Java, or C++.
Solid knowledge of software engineering and data science techniques and methodologies and demonstrated ability to apply these methodologies in active projects.
Solid experience in integrating applications with cloud technologies such as AWS.
Successfully deployed multiple ML models in production environments.
Good communication and presentation skills. Ability to convey complicated technical topics to non-technical people both verbally and in writing.

Nice to have

Expertise in MLOps frameworks such as MLflow and Kubeflow.
Comfort with Python-based frameworks such as PyTorch, TensorFlow, and scikit-learn is a plus.
Interest in cybersecurity applications.

Culture & Benefits

Competitive benefits and salaries.
Personal and professional development opportunities.
Flexibility.