Machine Learning Engineer | Remote - Contract

Xperteez Technology Pvt Ltd; United States; Remote; USD 83,000 - 131,000; Part time

Job summary

Xperteez Technology Pvt Ltd is seeking a remote Contract Machine Learning Engineer to contribute to a dynamic client project. You will design and train models, using Python and ML libraries, to shape how systems learn and perform.

You'll analyze data with MongoDB, collaborate with cross-functional teams, evaluate models, tune hyperparameters, and document experiments to ensure repeatable workflows. This remote role welcomes candidates who thrive in fast-paced environments.

Qualifications

• Proficiency with Python and ML frameworks such as scikit-learn, TensorFlow, or PyTorch.
• Hands-on experience with MongoDB in ML projects.
• Strong problem-solving and a track record of delivering ML solutions in real-world settings.
• Understanding of model evaluation metrics, feature engineering, and data preprocessing techniques.
• Experience deploying or operationalizing ML models in cloud or enterprise environments.
• Clear written documentation and communication skills for sharing technical findings.
• Ability to adapt quickly to evolving project requirements and work in a remote setting.

Responsibilities

• Design, develop, and refine machine learning models using Python and relevant libraries to address project objectives.
• 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 thorough model evaluation, tuning hyperparameters, and benchmarking 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.

Skills

Python

Machine Learning

Tools

MongoDB

Job description

Role Title: Machine Learning Engineer Role Type: Contract Location: Remote

We are engaging Machine Learning Engineers to contribute expertise to a dynamic customer project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input.

Required Skills

• Python
• Machine Learning
• MongoDB

Scope of Work

• Design, develop, and refine machine learning models using Python and relevant libraries to address project objectives.
• 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 thorough model evaluation, tuning hyperparameters, and benchmarking 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.

Preferred Qualifications

• 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.

Originally posted on Himalayas