[Remote] Machine Learning Engineer
Note: The job is a remote job and is open to candidates in USA. CareerUS Solutions is seeking a talented Machine Learning Engineer to join their growing AI team. In this role, you'll design, build, deploy, and optimize machine learning models that power intelligent products and data-driven decision-making.
Responsibilities
- Design, develop, train, and deploy production-grade machine learning models
- Build scalable ML pipelines for data preprocessing, feature engineering, training, validation, and deployment
- Develop predictive models using supervised, unsupervised, and deep learning techniques
- Optimize model accuracy, latency, scalability, and reliability
- Collaborate with software engineering teams to integrate ML solutions into production applications
- Monitor model performance and implement retraining strategies
- Perform feature engineering and data analysis on structured and unstructured datasets
- Work with cloud-based ML platforms and distributed computing frameworks
- Develop APIs and services for model inference
- Implement MLOps best practices including CI/CD, model versioning, and automated deployment
- Stay current with emerging AI and machine learning technologies
- Document technical solutions and mentor junior engineers when needed
Skills
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, Mathematics, Statistics, or a related field
- 5+ years of professional experience in Machine Learning Engineering or AI development
- Strong programming experience in Python
- Experience developing and deploying machine learning models in production
- Strong understanding of supervised, unsupervised, reinforcement learning, and deep learning concepts
- Experience with large datasets and feature engineering
- Knowledge of model evaluation, optimization, and hyperparameter tuning
- Experience building REST APIs for ML services
- Strong problem-solving and analytical skills
- Excellent communication and collaboration abilities
- Experience with Large Language Models (LLMs) and Generative AI
- Experience working with Retrieval-Augmented Generation (RAG)
- Experience fine-tuning transformer models
- Knowledge of Vector Databases
- Experience deploying AI solutions on cloud platforms
- Familiarity with Kubernetes and containerized ML deployments
- Experience with real-time inference systems
- Contributions to open-source AI or machine learning projects
Company Overview