Machine Learning Engineer

W2 Only

for W2 Candidates

Job Summary:

We are seeking a highly motivated Machine Learning Engineer to join our team. You will be responsible for developing, deploying, and optimizing machine learning models that help solve real-world problems. You will collaborate closely with data scientists, engineers, and product teams to turn data into actionable insights and intelligent systems.

Key Responsibilities:

• Design, build, and deploy scalable machine learning models for classification, regression, recommendation, NLP, or computer vision tasks.
• Collaborate with data scientists and software engineers to integrate models into production environments.
• Optimize model performance using techniques like hyperparameter tuning, feature engineering, and data augmentation.
• Evaluate and monitor deployed models to ensure long-term accuracy and relevance.
• Stay current with the latest research and industry trends in machine learning and AI.
• Develop data pipelines and tools for training and validating machine learning models.
• Write clean, maintainable, and well-documented code.

Required Qualifications:

• Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or a related field.
• Strong proficiency in Python and ML libraries such as scikit-learn, TensorFlow, PyTorch, or XGBoost.
• Experience working with large datasets and data processing tools (e.g., Pandas, NumPy, SQL, Spark).
• Solid understanding of machine learning algorithms and statistical modeling techniques.
• Experience with version control (e.g., Git) and software development best practices.

Preferred Qualifications:

• Experience deploying ML models using AWS, Azure, or Google Cloud Platform.
• Familiarity with MLOps practices and tools like MLflow, Kubeflow, or Airflow.
• Knowledge of deep learning architectures (CNNs, RNNs, Transformers).
• Exposure to DevOps, CI/CD pipelines, and containerization (Docker, Kubernetes).
• Publications or contributions to open-source ML projects.

Benefits:

• Competitive salary and performance bonuses
• Flexible work schedule and remote options
• Health, dental, and vision insurance
• Professional development budget and learning opportunities
• Friendly and innovative team environment