Deskripsi Pekerjaan
Are you a visionary Senior AI/Machine Learning Engineer with a passion for transforming complex data into intelligent solutions? CogniSphere Labs is at the forefront of AI innovation, building next-generation platforms that redefine industries. We're seeking a brilliant mind to join our elite team in San Francisco, where you'll design, develop, and deploy cutting-edge ML models that drive our core products.
At CogniSphere, you'll collaborate with world-class data scientists, software engineers, and product managers in a dynamic, fast-paced environment. This is an unparalleled opportunity to make a significant impact, working on challenging problems that directly influence our strategic direction and deliver tangible value to our customers. If you thrive on pushing the boundaries of what's possible with AI, we want to hear from you.
We offer a vibrant culture of continuous learning, professional growth, and a commitment to excellence. Join us and shape the future of artificial intelligence.
Tanggung Jawab
- Lead the design, development, and deployment of scalable machine learning models and algorithms.
- Collaborate with product teams to identify opportunities for AI integration and translate business requirements into technical specifications.
- Conduct extensive data analysis, feature engineering, and model evaluation to ensure optimal performance.
- Implement MLOps best practices for model versioning, deployment, monitoring, and retraining.
- Research and evaluate new AI/ML technologies, frameworks, and methodologies to maintain competitive advantage.
- Mentor junior engineers and contribute to the growth of our machine learning engineering team.
- Optimize existing machine learning pipelines for efficiency, cost-effectiveness, and real-time inference.
- Present findings, insights, and solutions to technical and non-technical stakeholders.
Kualifikasi
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- 5+ years of professional experience in developing and deploying machine learning solutions in production environments.
- Proficiency in Python and extensive experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Strong understanding of various machine learning algorithms (e.g., deep learning, NLP, computer vision, reinforcement learning) and statistical modeling.
- Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
- Demonstrated ability to build robust, scalable, and maintainable data and ML pipelines.
- Excellent problem-solving skills, with a track record of tackling complex technical challenges.
- Strong communication and collaboration skills, with the ability to articulate complex technical concepts clearly.