What you will do:

• Lead the development of end-to-end machine learning models, including data preprocessing, model training, evaluation, and deployment.
• Collaborate with data scientists, engineers, and product teams to define and implement ML algorithms that improve hiring accuracy and reduce bias.
• Architect scalable machine learning solutions that can process large datasets with high efficiency and reliability.
• Optimize and fine-tune models to enhance predictive accuracy, minimize bias, and ensure ethical AI practices.
• Conduct experiments, A/B testing, and validate ML model performance in a production environment.
• Mentor junior ML engineers and interns, providing guidance and support to develop their skills.

What makes you a great fit:

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or related field (Ph.D. is a plus).
• 3+ years of experience in machine learning, with a focus on supervised and unsupervised learning, deep learning, and NLP techniques.
• Proficient in Python, TensorFlow, PyTorch, or other ML frameworks.
• Experience with data processing tools and big data platforms like Spark, Hadoop, and experience deploying ML models in cloud environments (AWS, GCP, Azure).
• Solid understanding of model evaluation metrics, bias mitigation techniques, and ethical AI practices.
• Strong analytical and problem-solving skills, with the ability to work in a collaborative team environment."