AI Summary
Seeking a skilled Machine Learning Engineer to design, develop, and deploy scalable ML solutions. The role requires expertise in ML algorithms, data engineering, and cloud technologies. Candidate must have 5+ years of experience and strong programming skills in Python.
Key Highlights
5+ years of experience in Machine Learning Engineering or Data Science
100% Remote position
Experience with ML frameworks like TensorFlow, PyTorch, Scikit-Learn, XGBoost
Key Responsibilities
Design, develop, and deploy machine learning models for predictive analytics, classification, recommendation systems, and NLP applications
Build and optimize end-to-end ML pipelines for data ingestion, feature engineering, model training, validation, and deployment
Collaborate with Data Scientists, Data Engineers, and business stakeholders to translate business requirements into ML solutions
Develop and maintain scalable APIs and microservices for model serving
Monitor model performance, retrain models, and implement MLOps best practices
Work with large-scale structured and unstructured datasets
Optimize model accuracy, scalability, and reliability in production environments
Implement CI/CD pipelines for ML model deployment and lifecycle management
Technical Skills Required
Benefits & Perks
401(k) matching
Dental insurance
Health insurance
100% Remote
Job Description
Benefits:
- 401(k) matching
- Dental insurance
- Health insurance
100% Remote
We are seeking a highly skilled Machine Learning Engineer to design, develop, deploy, and maintain scalable machine learning solutions that drive business value. The ideal candidate will have strong expertise in machine learning algorithms, data engineering, model deployment, and cloud technologies.
Key Responsibilities:
Interested in remote work opportunities in Machine Learning & AI? Discover Machine Learning & AI Remote Jobs featuring exclusive positions from top companies that offer flexible work arrangements.
- Design, develop, and deploy machine learning models for predictive analytics, classification, recommendation systems, and NLP applications.
- Build and optimize end-to-end ML pipelines for data ingestion, feature engineering, model training, validation, and deployment.
- Collaborate with Data Scientists, Data Engineers, and business stakeholders to translate business requirements into ML solutions.
- Develop and maintain scalable APIs and microservices for model serving.
- Monitor model performance, retrain models, and implement MLOps best practices.
- Work with large-scale structured and unstructured datasets.
- Optimize model accuracy, scalability, and reliability in production environments.
- Implement CI/CD pipelines for ML model deployment and lifecycle management.
Browse our curated collection of remote jobs across all categories and industries, featuring positions from top companies worldwide.
- 5+ years of experience in Machine Learning Engineering or Data Science.
- Strong programming skills in Python.
- Experience with ML frameworks such as TensorFlow, PyTorch, Scikit-Learn, XGBoost.
- Strong understanding of machine learning algorithms, statistics, and data structures.
- Experience with SQL, data processing, and feature engineering.
- Hands-on experience with cloud platforms such as AWS, Azure, or GCP.
- Experience with Docker, Kubernetes, CI/CD pipelines, and MLOps tools.
- Knowledge of REST APIs, microservices architecture, and model deployment.
- Experience working with distributed computing frameworks such as Spark.
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