Senior Machine Learning Engineer

Job Title: Senior Machine Learning Engineer

Location: Remote

Job Type: Contract

About Us:

Infinite Uptime uses advanced predictive maintenance analytics and interconnected data to surface actionable insights. These empower intelligent, data-driven decisions, driving continuous improvement and optimizing performance with our predictive maintenance solutions.

Job Description:

We are looking for an experienced Senior Machine Learning Engineer with a strong background in developing and deploying machine learning models to solve real-world problems. The ideal candidate will have 5+ years of expertise in machine learning, deep learning, and data science, with hands-on experience working with complex real-time data. You will be responsible for designing and optimizing ML models, deploying them in production, and continuously improving their performance based on field feedback.

Key Responsibilities:

• Conduct feature engineering , data analysis , and data exploration to extract valuable insights.
• Develop and optimize Machine Learning models to achieve high accuracy and performance.
• Design and implement Deep Learning models , including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques.
• Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness.
• Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback.
• Collaborate with cross-functional teams to align ML solutions with business goals .
• Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models.
• Bring in latest advancements in ML and AI to drive innovation.

Requirements:

• 5+ years of hands-on experience in Machine Learning and Deep Learning.
• Strong expertise in feature engineering, data exploration, and data preprocessing .
• Experience with imbalanced datasets and techniques to improve model generalization.
• Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks .
• Strong mathematical and statistical knowledge with problem solving skills
• Ability to optimize models for high accuracy and performance in real-world scenarios.

Preferred Qualifications:

• Experience with Big Data technologies (Hadoop, Spark, etc. ).
• Familiarity with containerization and orchestration tools (Docker, Kubernetes).
• Experience in automating ML pipelines with MLOps practices.
• Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Why Join Us?

• Opportunity to work on cutting-edge ML solutions with real-world impact.
• A collaborative and innovative work environment.

If youre passionate about Machine Learning and want to make a real difference, wed love to hear from you!