Senior AI Engineer, Reinforcement Learning (Post-training)

We are in search of a highly experienced Senior AI Engineer to expedite the implementation of enhancements to our models. The chosen candidate will collaborate with diverse teams focused on various aspects of the system, including core functionalities, integrating multimodal components such as code, text, and images, tools, and more. This role presents an exceptional opportunity to influence the evolution of the Internet Computer by engaging with the technology stack across various levels, from fine-tuning low-level elements like GPU kernels to mastering post-training reinforcement learning intricacies.

The perfect candidate should possess a strong technical background encompassing areas such as data technologies, reliable software engineering, production of ML models, and cross-functional teamwork. While research background is optional, a profound knowledge of ML fundamentals and large-scale deep learning is crucial for effectively addressing complex system and ML-related challenges. Excellent verbal and written communication skills, as well as solid project management capabilities, are vital as you will actively engage with both technical engineering and research teams, alongside non-technical product teams within the organization.

Responsibilities

• Ownership of Post-Training Pipeline: Lead the design, execution, and enhancement of the post-training pipeline to ensure efficient model implementation and scalability.
• Data Development Coordination: Supervise the creation of high-quality training datasets, encompassing managing synthetic data production and utilization.
• Model Training: Conduct advanced model training to drive continuous enhancements in accuracy and performance.
• Collaboration: Engage closely with cross-functional teams like data engineers, software engineers, and product teams to seamlessly integrate AI models into production.
• Performance Monitoring: Evaluate and oversee the performance of deployed models, continuously refining training pipelines to bolster outcomes.

Requirements

• Experience: At least 5 years of experience in AI/ML engineering, with a specialization in model training and deployment.
• Post-Training Proficiency: Demonstrated proficiency in constructing and optimizing post-training pipelines at scale.
• Data Coordination: Proficient in managing the development and annotation of both synthetic and real-world datasets.
• Technical Skills: Strong proficiency in Python, TensorFlow/PyTorch, and experience with cloud platforms like AWS, GCP, or Azure.
• Team Leadership: Established track record of coordinating intricate engineering projects involving cross-functional teams.
• Analytical Skills: Robust problem-solving capabilities focusing on performance enhancement and automation.

Bonus Points

• Previous exposure to distributed AI systems.
• Hands-on involvement with synthetic data generation and augmentation methods.
• Familiarity with tools facilitating data pipeline automation and orchestration.

About DFINITY and the Internet Computer

DFINITY plays a pivotal role in the development of the Internet Computer Protocol (ICP), aiming to migrate global compute operations to the secure ICP network. Leveraging next-generation blockchain technology, ICP empowers the creation and operation of a new wave of unstoppable, tamper-proof, fully decentralized applications on the web. Its cutting-edge technology enables the execution of complete AI models within smart contracts, a groundbreaking feat for secure AI advancement. Through seamless integration with prominent networks like Bitcoin and Ethereum, ICP facilitates multi-chain digital asset operations and web3 development.

Join our team comprising over 250 talented individuals, inclusive of renowned cryptographers, distributed systems engineers, programming language experts, and thought leaders, dedicated to molding the future of the internet and web3.

DFINITY was established in 2016 by entrepreneur and crypto visionary Dominic Williams.

All qualified applicants will be considered for employment, regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.