ML Engineer

We are looking for a highly skilled Machine Learning Engineer to join our AI/ML team and build production-ready machine learning solutions for real-world business problems. The candidate will work closely with data scientists, software engineers, data engineers, and product teams to develop, deploy, and continuously improve machine learning models and systems.

Key Responsibilities

• Design, develop, train, and deploy machine learning models.
• Build scalable ML pipelines for data preparation, training, evaluation, and inference.
• Perform feature engineering, model selection, and hyperparameter optimization.
• Evaluate and improve model accuracy, performance, and scalability.
• Deploy and maintain machine learning models in production.
• Develop APIs and services to integrate ML models with business applications.
• Implement model monitoring, versioning, and retraining processes.
• Collaborate with data and software engineering teams on end-to-end ML solutions.
• Apply MLOps practices to improve the reliability and maintainability of ML systems.
• Contribute to technical architecture and design decisions.
• Mentor junior engineers and promote best engineering practices.
• Stay up to date with advancements in machine learning, deep learning, and AI technologies.

Skills and qualifications

• Impeccable analytical and problem-solving skills
• Extensive math and computer skills, with a deep understanding of probability, statistics, and algorithms
• In-depth knowledge of machine learning frameworks, like Keras or PyTorch
• Familiarity with data structures, data modeling, and software architecture
• Excellent time management and organizational skills

This role

Team ML

Type Full-time

Location Canada(Toronto, Vancouver)/Hybrid , India(Bangalore)/Hybrid, USA(Fremont-California)/Hybrid

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.