Deskripsi Pekerjaan
About CogniTech Innovations: At CogniTech Innovations, we are at the forefront of artificial intelligence, building intelligent systems that redefine industries. Our mission is to harness the power of AI to solve complex challenges and create groundbreaking solutions that enhance human capabilities and drive progress. We foster a collaborative, innovative, and fast-paced environment where brilliant minds come together to shape the future.
The Opportunity: We are seeking a highly skilled and passionate AI Engineer to join our dynamic R&D team in San Francisco. This is an unparalleled opportunity to work on cutting-edge AI projects, from concept to deployment, impacting millions. You will be instrumental in designing, developing, and deploying robust AI models and scalable machine learning systems that power our next-generation products. If you are a visionary problem-solver with a deep understanding of AI principles and a drive to innovate, we want to hear from you.
Join us and contribute to a legacy of innovation!
Tanggung Jawab
- Design, develop, and implement advanced AI/ML models and algorithms.
- Build and optimize scalable machine learning pipelines for data ingestion, training, and inference.
- Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to define project requirements and deliver integrated solutions.
- Evaluate and select appropriate AI/ML frameworks, tools, and technologies.
- Conduct rigorous testing, evaluation, and fine-tuning of models to ensure optimal performance and accuracy.
- Deploy AI models into production environments and monitor their performance, making iterative improvements.
- Research and stay abreast of the latest advancements in AI, machine learning, and deep learning.
Kualifikasi
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- 3+ years of professional experience in developing and deploying AI/ML solutions in a production environment.
- Proficiency in programming languages such as Python (with libraries like TensorFlow, PyTorch, scikit-learn), Java, or C++.
- Strong understanding of machine learning algorithms (e.g., supervised, unsupervised, reinforcement learning) and deep learning architectures (e.g., CNNs, RNNs, Transformers).
- Experience with cloud platforms like AWS, GCP, or Azure for MLOps and infrastructure.
- Familiarity with data processing and manipulation tools (e.g., Pandas, SQL).
- Excellent problem-solving skills and the ability to translate complex business problems into AI solutions.
- Strong communication skills and ability to work effectively in a team-oriented environment.