ML Infrastructure Engineer
Description For ML Infrastructure Engineer
Gatik, a pioneering force in autonomous middle-mile logistics, is revolutionizing the B2B supply chain with its autonomous transportation-as-a-service solution. As the first company to achieve fully driverless commercial deliveries, Gatik operates across major markets including Texas, Arkansas, and Ontario. We're seeking a skilled ML Infrastructure Engineer to join our innovative team.
In this role, you'll be at the forefront of building and maintaining scalable distributed ML training and inference systems. You'll work with cutting-edge technology, designing and refining data and ML pipelines for distributed training and validation of ML models. This position offers the unique opportunity to work alongside experts in AI, robotics, and software engineering, pushing the boundaries of autonomous trucking technology.
Founded in 2017, Gatik has established itself as a leader in the autonomous vehicle industry, with a clear focus on middle-mile logistics for Fortune 500 retailers. Our proprietary Level 4 autonomous technology, Gatik Carrier™, is specifically designed for safe and efficient freight transport between pick-up and drop-off locations.
The ideal candidate brings strong expertise in ML infrastructure, distributed systems, and a passion for autonomous driving technology. You'll have the opportunity to work on challenging problems in a collaborative environment, contributing to the future of autonomous transportation while being part of a diverse and inclusive team committed to creating a more resilient supply chain.
Responsibilities For ML Infrastructure Engineer
- Lead exploration of distributed training and inference optimization
- Build scalable distributed ML training and inference pipelines
- Develop model benchmarking processes and tools
- Accelerate machine learning development and maximize hardware utilization
- Develop infrastructure for data augmentation pipelines
- Collaborate with AI Research and DevOps teams
- Integrate state-of-the-art open-source AV models into pipelines
Requirements For ML Infrastructure Engineer
- 3+ years of production or research experience in ML Infra
- Understanding of deep learning algorithms
- Familiarity with Azure/AWS/GCP cloud products
- Proficiency with Kubernetes clusters
- Experience with DDP and model parallelization
- Strong foundation in data structures and algorithms
- Expertise in Python/C++ and deep learning frameworks
- Strong communication and teamwork skills
- Passion for Autonomous Driving
Benefits For ML Infrastructure Engineer
- Diverse and inclusive work environment
- Opportunity to work on cutting-edge autonomous vehicle technology
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