Machine Learning Engineer

Accountabilities:

• Design, develop, and maintain scalable AI/ML services and pipelines in cloud-based environments.

• Build and optimize machine learning workflows, including data preparation, curation, annotation, training, validation, and deployment.

• Contribute to research and development initiatives involving emerging AI frameworks, models, and technologies.

• Deploy and support production-grade machine learning systems with a strong focus on reliability, scalability, and performance.

• Troubleshoot and resolve issues in mission-critical production environments following an end-to-end ownership mindset (“you build it, you run it”).

• Develop vision-based AI solutions, including object detection, image segmentation, labeling, and classification tasks.

• Collaborate with cross-functional and distributed teams to deliver high-quality, production-ready AI solutions.

• Continuously improve system architecture, model performance, and operational efficiency through experimentation and optimization.

Requirements:

• 3+ years of hands-on experience in Python development.

• 4+ years of experience in machine learning, deep learning, or large language model-based systems.

• Strong experience working with cloud platforms (preferably AWS) for building and deploying AI/ML pipelines.

• Experience designing scalable workflows for data ingestion, processing, labeling, and secure storage for model training.

• Proven experience in training, fine-tuning, testing, and deploying machine learning models in production environments.

• Solid understanding of computer vision techniques such as object detection, segmentation, and image classification.

• Strong problem-solving skills with the ability to design scalable, fault-tolerant, and efficient systems.

• Experience working independently and collaboratively in distributed, remote-first teams.

• Excellent communication skills for effective collaboration across global engineering teams.

• Familiarity with tools such as AWS SageMaker, AWS Bedrock, or NVIDIA AI platforms is a plus.

• Exposure to media, audio, video, or image processing workflows is considered an advantage.

Benefits:

• Competitive compensation based on skills and experience, with performance-based adjustments.

• Fully remote work with flexible scheduling across global time zones.

• Opportunity to work with cutting-edge AI, ML, and cloud technologies.

• Continuous learning and professional development support, including paid training opportunities.

• Exposure to challenging, high-impact projects in a global engineering environment.

• Long-term engagement with a steady flow of meaningful and technically challenging work.

• Recognition and rewards based on performance and contribution.

• Freedom to work from anywhere with a stable internet connection.

• Inclusive and diverse international team culture.

How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
 Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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