Description

You will design, build, and deploy end-to-end machine learning systems to solve complex business problems.

Responsibilities

• Develop, train, and optimize machine learning models using appropriate algorithms and frameworks.
• Design and implement ML pipelines including data preprocessing, feature engineering, and deployment.
• Deploy and monitor models in production environments to ensure performance, reliability, and scalability.
• Collaborate with data scientists and software engineers to integrate ML models into applications.
• Perform data analysis, visualization, and validation to maintain data quality and model accuracy.

Required Skills

• 3+ years of experience in machine learning engineering or data science.
• Strong programming skills in Python.
• Proficiency with ML libraries including TensorFlow, PyTorch, scikit-learn, or XGBoost.
• Experience with data processing frameworks such as Pandas, NumPy, and SQL.
• Knowledge of supervised, unsupervised, and reinforcement learning algorithms.
• Familiarity with cloud platforms including AWS, Azure, or GCP.
• Experience with containerization using Docker and Kubernetes.
• Experience deploying models via REST APIs, microservices, or serverless architectures.
• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Statistics, or a related field.

Preferred Skills

• Experience with NLP, computer vision, or deep learning techniques.
• Familiarity with big data technologies like Spark or Hadoop.
• Understanding of MLOps practices and tools such as MLflow, Kubeflow, or Airflow.

Key Skills

Education

Bachelor’s or Master’s degree