AI Engineer in ML Data

Logical Intelligence is revolutionizing software development with AI-powered formal verification. As an AI Engineer, you will design and refine data and ML pipelines for scaled distributed training and validation of ML models while collaborating with a talented team to create groundbreaking solutions.

Responsibilities:

• 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

Requirements:

• 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
• Demonstrated publications in any of the major conferences
• Multi-node and multi-GPU training
• Mathematical Reasoning – discrete math and logic
• Formal Verification - lean