Deskripsi Pekerjaan
Are you a visionary Machine Learning Engineer passionate about building scalable AI platforms that redefine industries? Innovate AI Labs is seeking a talented and experienced Senior Machine Learning Engineer to join our dynamic team in San Francisco. We're at the forefront of AI innovation, tackling complex challenges with cutting-edge solutions across various sectors.
At Innovate AI Labs, you'll be instrumental in designing, developing, and deploying high-performance machine learning models and infrastructure. You'll work on greenfield projects, contribute to the entire ML lifecycle, from research and experimentation to production deployment and monitoring. If you thrive in a collaborative environment, love pushing technological boundaries, and want to see your work make a tangible impact, we want to hear from you!
Join us and contribute to a culture of innovation, continuous learning, and impactful AI development.
Tanggung Jawab
- Design, develop, and implement robust and scalable machine learning models and algorithms.
- Build and maintain MLOps pipelines for efficient model training, deployment, and monitoring in production.
- Collaborate with data scientists and product managers to translate business problems into technical ML solutions.
- Conduct extensive research and experimentation to explore new machine learning techniques and tools.
- Optimize existing models for performance, accuracy, and efficiency using various techniques.
- Ensure the ethical and responsible development and deployment of AI systems.
- Mentor junior engineers and contribute to a culture of technical excellence and knowledge sharing.
Kualifikasi
- Master's or Ph.D. in Computer Science, Machine Learning, AI, Statistics, or a related quantitative field.
- 5+ years of professional experience in Machine Learning Engineering, with a strong focus on production systems.
- Proficiency in Python and relevant ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
- Demonstrated experience with cloud platforms (AWS, GCP, Azure) for ML infrastructure.
- Solid understanding of data structures, algorithms, and software engineering best practices.
- Experience with MLOps tools and practices (e.g., Kubeflow, MLflow, Docker, Kubernetes).
- Excellent problem-solving skills and the ability to work independently and as part of a team.
- Strong communication skills, with the ability to articulate complex technical concepts to diverse audiences.