Deskripsi Pekerjaan
Join QuantumLeap AI, a pioneering force in artificial intelligence, and shape the future of intelligent systems. We are seeking a highly skilled and innovative Senior Machine Learning Engineer to lead cutting-edge research and development within our AI Innovation Lab. This is an exceptional opportunity to work on complex, impactful projects, mentor junior engineers, and contribute to groundbreaking advancements in areas like natural language processing, computer vision, and reinforcement learning. If you're passionate about pushing the boundaries of AI and thrive in a collaborative, fast-paced environment, we want to hear from you!
At QuantumLeap AI, we foster a culture of continuous learning, experimentation, and excellence. You'll have access to state-of-the-art resources and collaborate with some of the brightest minds in the industry.
Tanggung Jawab
- Design, develop, and deploy advanced machine learning models and algorithms for complex problems.
- Lead research initiatives, explore novel ML techniques, and stay abreast of the latest advancements in the field.
- Architect and implement scalable and efficient ML pipelines for training, evaluation, and deployment.
- Collaborate closely with cross-functional teams (data scientists, software engineers, product managers) to define project requirements and deliver impactful solutions.
- Mentor and guide junior ML engineers, fostering a culture of technical growth and knowledge sharing.
- Optimize model performance, ensuring robustness, efficiency, and accuracy.
- Contribute to the strategic direction of the AI Innovation Lab and identify new opportunities for AI application.
Kualifikasi
- Master's or Ph.D. in Computer Science, Artificial Intelligence, or a related quantitative field.
- 5+ years of professional experience in machine learning engineering with a strong portfolio of successfully deployed models.
- Expertise in at least one major deep learning framework (e.g., TensorFlow, PyTorch).
- Proficiency in programming languages such as Python, and experience with ML libraries (e.g., Scikit-learn, XGBoost).
- Solid understanding of statistical modeling, probability, and linear algebra.
- Experience with cloud platforms (AWS, GCP, Azure) and MLOps best practices.
- Excellent problem-solving, analytical, and communication skills.
- Proven ability to lead projects and mentor team members.