Logical Intelligence
Posted 69 days agoVerified live 2d ago
AI Engineer in ML Data
Brief overview
Remote
MastersOr in progress
3+ yrsMinimum
Machine Learning InfrastructureDataOpsDistributed TrainingPythonC++PyTorchTensorFlowJAXDeep Learning AlgorithmsNatural Language ProcessingAzure CloudAWS CloudGCP CloudKubernetesMulti-node TrainingMulti-GPU TrainingMathematical Reasoning
About the company
Logical Intelligencelogicalintelligence.com
Logical Intelligence develops energy-based AI systems for reasoning in mission-critical industrial and infrastructure environments.
Job description
Summary
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
Skills
- 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
Qualifications
Must Haves
- 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
Nice to Haves
- Demonstrated publications in any of the major conferences
- Multi-node and multi-GPU training
- Mathematical Reasoning – discrete math and logic
- Formal Verification - lean
