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Senior Machine Learning Engineer

Remote:

Full Remote

Contract:

Full time

Experience:

Senior (5-10 years)

Work from:

Brazil

Offer summary

Qualifications:

Proven experience in machine learning engineering, Proficiency in Python and core data science skills, Experience with cloud platforms like AWS, Understanding of software engineering practices.

Key responsabilities:

Build and deploy scalable machine learning models
Develop and maintain end-to-end machine learning pipelines

TRACTIAN 𝗕𝗥 Scaleup https://tractian.com/

51 - 200 Employees

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Job description

Data Science at TRACTIAN

The Data Science team at TRACTIAN focuses on extracting valuable insights from vast amounts of industrial data. Using advanced statistical methods, algorithms, and data visualization techniques, this team transforms raw data into actionable intelligence that drives decision-making across engineering, product development, and operational strategies. The team constantly works on optimizing prediction models, identifying trends, and providing data-driven solutions that directly enhance the company’s operational efficiency and the quality of its products.

What you'll do

We are seeking a Machine Learning Engineer to solve complex data challenges and build ML solutions. The position requires strong foundational skills in ML engineering and data science, with the ability to design and deploy models that address diverse problems. While optimization experience is a valuable addition, it is not a mandatory requirement for the role.

Responsibilities

Build and deploy scalable machine learning models.

Develop and maintain end-to-end machine learning pipelines.

Collaborate with data scientists and engineers to integrate ML solutions into production systems.

Analyze and preprocess data to support model development.

Optimize models for performance, scalability, and efficiency.

Requirements

Proven experience in machine learning engineering, including deployment and monitoring.

Proficiency in Python and core data science skills such as clustering, classification, and regression. A plus is a knowledge of working with images and texts.

Experience with cloud platforms and containerization tools (e.g., AWS, Docker).

Understanding of software engineering practices (version control, testing, CI/CD).

Preferred (Plus):

Background in mathematical programming, operational research, or optimization techniques.

Experience with combinatorial optimization, linear programming, or mixed-integer programming.