Lead ML Engineer

Role Summary
The Lead ML Engineer will be responsible for designing, developing, and implementing cutting-edge machine learning (ML) and large language model (LLM) solutions that enhance Kingsley Gate Partners' decision-making processes. This individual will lead a small team of ML engineers and data scientists, driving the development of scalable and efficient ML pipelines while mentoring junior team members.
Responsibilities
Lead the end-to-end development of machine learning models to drive business impact.
Collaborate with cross-functional teams to translate business needs into ML solutions.
Optimize models for performance, scalability, and accuracy.
Design robust data pipelines for ingestion, preprocessing, and feature engineering.
Stay updated with ML advancements and apply innovative solutions.
Ensure model reliability through rigorous testing and validation.
Contribute to best practices for ML development, deployment, and maintenance.
Mentor junior engineers and foster a culture of learning.
Integrate ML solutions into existing systems and applications.
Maintain high standards of security, privacy, and ethical AI practices.

Required Skills & requirements:
5-7 years in ML engineering with minimum 3 years of team leadership.
Hands-on experience with LLMs, Python, and one of Java/C++ and experience with machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn.
Proven experience with machine learning algorithms, deep learning techniques, and artificial intelligence applications.
Experience with cloud computing platforms (e.g.AWS, GCP, or Azure) and MLOps practices.
Strong communication and problem-solving skills.
Familiarity with agile software development methodologies and best practices for software engineering.
Education:
Bachelor's degree in Computer Science, Mathematics, Statistics, or a related field.
A Master's or Ph.D. in a relevant field is highly preferred.