What You'll Do
- AI Model Development: Design, develop, and optimize machine learning models (e.g., supervised/unsupervised learning, reinforcement learning, deep learning, NLP, etc.) to solve business challenges for our professionals.
- End-to-End AI Pipeline: Build and deploy end-to-end AI pipelines, from data preprocessing to model training, evaluation, and production deployment.
- Collaboration: Work alongside data scientists, software engineers, product managers, and other stakeholders to ensure AI solutions align with business goals and user needs.
- Research and Innovation: Stay up-to-date with the latest AI/ML research and integrate cutting-edge techniques into product development.
- Model Optimization: Continuously monitor, test, and improve models in production environments to ensure they perform optimally and meet business requirements.
- Mentorship: Provide technical leadership and mentorship to junior AI engineers, guiding them in best practices and new techniques.
- Scalability & Performance: Ensure AI systems are scalable, reliable, and capable of handling large-scale data and real-time processing requirements.
- Documentation & Reporting: Create comprehensive documentation of models, algorithms, and workflows, and present findings to technical and non-technical stakeholders.
At a Minimum, We'd Like You to Have
- Minimum of 5 years of professional experience in AI/ML engineering.
- Proven expertise in designing and deploying machine learning models at scale.
- Strong background in deep learning, reinforcement learning, NLP, or computer vision.
- Extensive experience with frameworks like TensorFlow, PyTorch, Keras, or similar.
- Familiarity with cloud platforms (AWS, GCP, Azure) for deploying AI solutions.
- Expertise in programming languages such as Python, C++, or Java.
- Strong mathematical and statistical knowledge, including probability, linear algebra, and optimization techniques.
- Experience with data engineering concepts, such as ETL processes, data pipelines, and handling large datasets.
- Familiarity with version control systems (Git) and CI/CD pipelines for AI/ML.
- Ability to translate complex technical concepts into clear, actionable insights for stakeholders.
- Strong problem-solving skills and the ability to think creatively to overcome technical challenges.
Ideally, You'll Also Have
- Experience with MLOps, model monitoring, and model lifecycle management.
- Knowledge of AI ethics and responsible AI practices.
- Familiarity with cutting-edge techniques in generative AI or multi-modal learning.
- Contributions to open-source AI projects or publications in top AI conferences/journals.

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