Remote Machine Learning Engineer

Description:

• The company is looking for a talented and motivated Machine Learning Engineer to join their team.
• The ideal candidate should have a strong background in machine learning and a passion for developing innovative solutions to enhance data annotation processes and tools.
• Responsibilities include developing, implementing, and optimizing machine learning models, collaborating with teams to understand client requirements, researching and applying state-of-the-art techniques, designing scalable data pipelines, conducting experiments for model evaluation, providing guidance to the annotation team, and staying updated with the latest trends in machine learning.
• The position involves working closely with data scientists, annotation teams, and clients to ensure high-quality data delivery.

Requirements:

• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field.
• Proven experience as a Machine Learning Engineer or similar role.
• Strong understanding of machine learning algorithms, models, and techniques.
• Proficiency in programming languages like Python, R, or Java.
• Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, etc.
• Knowledge of data preprocessing, feature engineering, and model evaluation.
• Familiarity with cloud platforms (AWS, Google Cloud, Azure) and big data technologies (Hadoop, Spark) is a plus.
• Excellent problem-solving skills and ability to work in a fast-paced environment.
• Strong communication and collaboration skills.
• Additional experience in the annotation or data labeling industry, computer vision, NLP techniques, advanced ML techniques, and quality assurance processes is a plus.

Benefits:

• Remote work opportunity.
• Flexible working hours.
• Competitive payment with commission.
• Opportunities for financial and professional growth.
• Great management without bureaucracy.
• Open, collaborative, and dynamic work culture.
• Inclusive international environment.
• Interesting and challenging tasks.