About the roleJoin our team as an AI Engineer and help us push the boundaries of what's possible in logical reasoning! We're looking for a motivated individual to design and refine the data and ML pipelines for scaled distributed training and validation of ML models. You'll work closely with a talented team of AI experts, EBM specialists, formal verification engineers, and software developers to create groundbreaking solutions.
What you'll do- Research new reasoning algorithms and models
- Develop model benchmarking processes and tools
- Build effective and efficient ML data pipelines
- Adjust frameworks and interfaces to accelerate machine learning development
- Develop the infrastructure for data augmentation pipelines and synthetic data generation
- Collaborate with other teams to understand their pain points and priorities to define milestones of the corresponding roadmaps
- Derive practical solutions and integrate them with the results of other teams to provide the best overall resolution
Qualifications- You have an M.Sc. focusing on one or more of the following areas: Computer Science, Artificial Intelligence, Mathematics, or a closely related field
- 3+ years of production experience in ML Infra, DataOps, distributed training
- Expertise in programming languages and tools critical for high-performance computing in Python/C++ and machine learning including Deep Learning frameworks like PyTorch /TensorFlow/JAX
- Ability to understand deep learning algorithms, e.g. in natural language processing, reasoning
- Familiarity with Azure/AWS/GCP cloud products for MLOps and DataOps pipelines
- Proficiency with Kubernetes clusters and distributed compute assets
- Strong communication and teamwork skills
- Readiness to explore and promote cutting edge technologies in ML Infrastructure domain and beyond
Bonus Points- Demonstrated publications in any of the major conferences
- Multi-node and multi-GPU training
- Mathematical Reasoning - discrete math and logic
- Formal Verification - lean
logicalintelligence.com
