Junior Machine Learning Engineer

Junior Machine Learning Engineer (1 year experience, hybrid)

Be part of our future! This job posting builds our talent pool for potential future openings. We'll compare your skills and experience against both current and future needs. If there's a match, we'll contact you directly. No guarantee of immediate placement, and we only consider applications from US/Canada residents during the application process.

Hiring Type: Full-Time

Base Salary: $56K-$66K Per Annum.

Summary:

As a Junior Machine Learning Engineer, you will have the opportunity to work on exciting projects, develop your skills, and contribute to the development and implementation of machine learning solutions. This is an excellent opportunity for individuals looking to kick-start their careers in the field of machine learning and gain valuable experience in a collaborative and supportive environment.

Responsibilities:

• Collaborate with senior engineers and data scientists to understand project requirements and develop machine learning models and algorithms.
• Assist in collecting, preprocessing, and analyzing data to uncover patterns and insights.
• Implement and optimize machine learning models, algorithms, and pipelines.
• Participate in model evaluation, validation, and performance tuning.
• Contribute to the development and improvement of existing machine learning infrastructure and frameworks.
• Stay up-to-date with the latest advancements in machine learning and actively participate in knowledge-sharing activities within the team.
• Collaborate with cross-functional teams to integrate machine learning solutions into production systems.
• Document technical processes, methodologies, and outcomes effectively.
  
  

Qualifications:

• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field.
• Solid understanding of machine learning fundamentals, algorithms, and statistical concepts.
• Proficiency in programming languages such as Python, Java, or C++.
• Familiarity with machine learning frameworks and libraries, such as TensorFlow, PyTorch, or scikit-learn.
• Experience with data preprocessing, feature engineering, and model evaluation techniques.
• Knowledge of deep learning architectures and techniques is a plus.
• Familiarity with big data processing tools (e.g., Hadoop, Spark) is advantageous.
• Strong problem-solving skills and the ability to work on multiple projects simultaneously.
• Excellent communication and collaboration skills.
• Self-motivated with a strong desire to learn and grow in the field of machine learning.