Senior Machine Learning Engineer — Full Time — Remote Full-time

Our client seeks an Senior Machine Learning Engineer for a Full Time in Remote. Below is the detailed requirement

Job Title: Senior Machine Learning Engineer

Location: USA – Remote
Employment Type: Full time

Experience: 8+ years

Job Summary:
We are seeking a highly skilled and experienced Senior Machine Learning Engineer to join our dynamic team. The ideal candidate will possess deep expertise in machine learning and natural language processing (NLP), along with strong software development skills. The role involves designing, developing, and deploying cutting-edge machine learning models, ensuring code quality, and contributing to the overall success of our AI-driven solutions.

Key Responsibilities:

• Develop and implement deep learning models using frameworks such as PyTorch, TensorFlow, or Keras.
• Build and optimize Natural Language Processing (NLP) solutions for various business applications.
• Ensure software development excellence by adhering to PEP-8 style code practices, and leveraging version control tools like Git.
• Collaborate with cross-functional teams to understand business needs and translate them into scalable solutions.
• Maintain and improve code readability, modularity, and reusability using advanced Python practices, including classes and decorators.
• Deploy and monitor models in production environments, ensuring their robustness and reliability.

Must-Have Skills:

• Minimum of 6 years of experience in machine learning and deep learning (Python, scikit-learn, XGBoost).
• Strong expertise in deep learning frameworks such as PyTorch, TensorFlow, and Keras.
• Hands-on experience in Natural Language Processing (NLP).
• Proficiency in software development practices, including Git, PEP-8 standards, and Python advanced programming techniques.

Preferred/Nice-to-Have Skills:

• Experience with Graph Neural Networks (GNN) and Graph Convolutional Networks (GCN).
• Knowledge of Reinforcement Learning techniques (e.g., PPO, DPO).
• Exposure to generative AI and large language models (LLMs).
• Experience building user interfaces with Streamlit or similar tools.
• MLOps expertise, including model deployment and full-stack development.
• Strong communication skills and ability to interface with business stakeholders effectively.