Deskripsi Pekerjaan
CogniTech Innovations is at the forefront of AI research and development, building intelligent systems that redefine industries. We are searching for an exceptional Senior Machine Learning Engineer to join our dynamic team in San Francisco. This is an unparalleled opportunity to design, develop, and deploy cutting-edge AI solutions that will impact millions.
As a Senior ML Engineer, you will be instrumental in pushing the boundaries of what's possible with machine learning, working on complex problems that require innovative thinking and a deep understanding of ML principles. You will collaborate with a diverse group of engineers, researchers, and product managers to bring groundbreaking AI products to life. If you are passionate about transforming data into intelligent action and thrive in a fast-paced, collaborative environment, we encourage you to apply!
Tanggung Jawab
- Lead the design, development, and deployment of scalable machine learning models and algorithms.
- Collaborate with cross-functional teams to identify opportunities for AI integration and product enhancement.
- Conduct research into new ML techniques and technologies to maintain our competitive edge.
- Optimize existing ML pipelines for performance, scalability, and cost-effectiveness.
- Mentor junior engineers, fostering a culture of technical excellence and continuous learning.
- Contribute to the entire ML lifecycle, from data collection and feature engineering to model deployment and monitoring.
- Participate in code reviews, ensuring high-quality, robust, and maintainable code.
- Present findings and progress to technical and non-technical stakeholders.
Kualifikasi
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related quantitative field.
- 5+ years of professional experience in machine learning engineering, with a strong portfolio of deployed models.
- Expertise in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Proficiency with cloud platforms (AWS, GCP, or Azure) for ML model deployment and management.
- Strong understanding of machine learning algorithms, deep learning architectures, and data structures.
- Experience with MLOps practices, including CI/CD for ML models and model monitoring.
- Excellent problem-solving skills and the ability to tackle complex, ambiguous challenges.
- Proven ability to work effectively in a collaborative team environment and communicate technical concepts clearly.