Machine Learning Engineer

Job not on LinkedIn

đŸ”„ 2 hours ago

🌏 Anywhere in the World

đŸ’” $80 - $140 / hour

⏰ Full Time

🟡 Mid-level

🟠 Senior

đŸ€– Machine Learning Engineer

đŸ‘» Ghost score 0%

infoinfo

Cloud

MongoDB

Python

PyTorch

Scikit-Learn

Tensorflow

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Logo of Your Software Supplier

Your Software Supplier

51 - 200 employees

Founded 2019

đŸ’Œ Consulting

📣 Marketing

đŸȘ Marketplace

💰 $50k Pre Seed Round - Your Software Supplier on 2019-08

Consulting ‱ Marketing ‱ Marketplace

Your Software Supplier is a B2B marketplace and matching service that connects clients with vetted software development suppliers for websites, mobile apps, custom software, AI solutions and staff augmentation. The platform provides free independent advice, a searchable supplier directory, shortlist matching (top-3), draft collaboration agreements, rough pricing guidance and consultancy to help clients kickstart projects and find developers or teams globally.

📋 Description

‱ Design, develop, and refine machine learning models using Python and relevant libraries ‱ Analyze large datasets and leverage MongoDB to manage and retrieve data efficiently for model training and validation ‱ Collaborate with cross-functional contributors to identify areas for model improvement and implement robust solutions ‱ Conduct model evaluation, tune hyperparameters, and benchmark results to ensure optimal performance ‱ Document methodologies, experiments, and outcomes to ensure transparent and repeatable workflows ‱ Integrate data pipelines and preprocessing workflows to streamline training and inference processes ‱ Deliver actionable insights and recommendations based on data-driven findings and machine learning outcomes

🎯 Requirements

‱ Demonstrated expertise with Python, including deep familiarity with machine learning frameworks such as scikit-learn, TensorFlow, or PyTorch ‱ Hands-on experience with MongoDB for data manipulation, storage, and retrieval within machine learning projects ‱ Strong problem-solving skills and a track record of delivering innovative ML solutions in real-world settings ‱ Understanding of model evaluation metrics, feature engineering, and effective data preprocessing techniques ‱ Background in deploying or operationalizing machine learning models in cloud or enterprise environments ‱ Clear written documentation and communication skills for sharing technical findings and best practices ‱ Ability to adapt quickly to evolving project requirements and contribute collaboratively in a remote setting

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