About the Role
We are seeking a Machine Learning Engineer to design, build, and deploy scalable ML models that power data-driven products and decisions. You will work closely with data scientists, software engineers, and product teams to take models from research to production in a fully remote environment.
Key Responsibilities
- Design, develop, and deploy machine learning models for production use
- Build and maintain scalable ML pipelines (data ingestion, training, evaluation, deployment)
- Collaborate with product and engineering teams to translate business requirements into ML solutions
- Optimize model performance, reliability, and scalability
- Monitor models in production and retrain as needed
- Conduct experiments and evaluate models using appropriate metrics
- Write clean, maintainable, and well-documented code
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field
- 3+ years of experience as a Machine Learning Engineer or similar role
- Strong proficiency in Python
- Experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn
- Solid understanding of machine learning algorithms, statistics, and data structures
- Experience with SQL and data manipulation tools
- Familiarity with software engineering best practices (version control, testing, CI/CD)
Preferred Qualifications
- Experience deploying ML models in production
- Knowledge of MLOps tools and workflows
- Experience with cloud platforms (AWS, GCP, or Azure)
- Familiarity with Docker, Kubernetes, and REST APIs
- Experience with big data tools (Spark, Kafka, Airflow)
- Background in NLP, computer vision, or recommendation systems
Tech Stack
- Python, SQL
- PyTorch / TensorFlow
- AWS / GCP / Azure
- Docker, Kubernetes
- Git, CI/CD pipelines
