This is a remote position.

We’re looking for a passionate and analytical Machine Learning Engineer to design, build, and deploy intelligent systems that turn data into actionable insights. In this role, you’ll collaborate with data scientists, software engineers, and product teams to develop scalable ML models that power real-world applications.

You’ll be deeply involved in the full lifecycle — from data preprocessing and experimentation to model optimization, deployment, and continuous improvement. This position is ideal for someone who thrives at the intersection of code, data, and innovation.

• Design, train, and evaluate machine learning and deep learning models for production environments.
  

• Build and optimize data pipelines and model-serving infrastructure.
  

• Work closely with product and engineering teams to translate business problems into ML solutions.
  

• Perform data cleaning, feature engineering, and exploratory data analysis.
  

• Monitor model performance, drift, and retraining cycles using MLOps best practices.
  

• Implement scalable APIs or microservices for model deployment.
  

• Stay current with the latest research and frameworks in AI/ML and suggest practical applications.
  

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, or related field.
  

• Strong programming skills in Python and experience with ML libraries (TensorFlow, PyTorch, Scikit-learn, etc.).
  

• Understanding of data structures, algorithms, and software engineering principles.
  

• Familiarity with cloud platforms (AWS, GCP, Azure) and containerization tools (Docker, Kubernetes).
  

• Experience with model versioning and CI/CD tools (MLflow, DVC, Airflow, etc.).
  

• Strong analytical mindset with the ability to interpret and communicate technical results.