Job Description
The Senior AI Infrastructure Engineer at Gatik is responsible for designing, building, and scaling high-performance AI platforms that support autonomous driving models, focusing on distributed training, model deployment, infrastructure automation, and system monitoring to enable efficient and reliable autonomous vehicle operations.
Key Responsibilities
- Design, build, and scale high-performance AI infrastructure for autonomous driving models
- Support distributed training and experiment tracking for complex ML models
- Optimize multi-GPU setups and low-level networking communication for large-scale training
- Deploy and scale optimized AI models using inference engines like TensorRT, ONNX Runtime, and Triton
- Develop and implement autonomous AI agents for infrastructure monitoring and hardware failure triage
- Create automation tools for infrastructure management, model lifecycle, and data curation
- Maintain and develop ML infrastructure leveraging MLFlow, Argo Workflows, and Kubernetes
- Scale and manage large data pipelines and ETL processes using Apache Airflow, Kafka, and Spark
- Implement monitoring and observability systems to track ML system metrics and infrastructure health
Requirements
- Five or more years of experience in ML infrastructure, MLOps, or DevOps supporting high-scale compute environments.
- Deep understanding of multi-GPU training strategies such as Fully Sharded Data Parallel (FSDP), DeepSpeed, Ray Train, and high-performance networking technologies including NCCL and InfiniBand.
- Mastery of Kubernetes, Terraform, and Helm, with a focus on GPU-native orchestration and infrastructure automation.
- Proven experience building or supporting Agentic Workflows for infrastructure or data automation, e.g., using large language models (LLMs) to drive DevOps tasks.
- Expertise in MLFlow, Argo Workflows, and Kubernetes for platform management.
- Strong experience with Docker, Kubernetes, and Helm for containerization.
- Proficiency in Apache Airflow, Kafka, Spark, and GitOps automation for data pipelines and CI/CD processes.
- Proficiency in Python and Bash scripting; experience with Go or Rust is a plus.
- Experience supporting or building autonomous AI agents such as LangGraph, CrewAI, or AutoGen for monitoring GPU cluster health and automating hardware failure triage.
- Experience designing, building, and scaling high-performance AI platforms that enable distributed training, experiment tracking, and model deployment.
- Ability to optimize low-level communication protocols such as NCCL, InfiniBand, or RoCE v2 to minimize latency for large-scale training.
- Ability to architect and optimize multi-GPU setups ensuring efficient model and data parallelism across clusters with H100 and A100 GPUs.
- Experience deploying and scaling models using TensorRT, ONNX Runtime, and Triton Inference Server, including fine-tuning pipelines for real-time and batch inference.
- Ability to develop agent-driven automation for infrastructure and data management, including model lifecycle automation and experiment tracking.
- Experience in scaling ETL pipelines using Apache Airflow, Kafka, and Spark, and collaborating with data engineering teams to manage large datasets in storage solutions like S3, GCS, or Delta Lake.
- Ability to define and track key ML system metrics such as training convergence, latency, throughput, and drift detection, and maintain deep visibility into platform health using Prometheus, Grafana, OpenTelemetry, and ELK Stack.
- Experience supporting or building systems for monitoring AI-specific KPIs including model latency, inference throughput, and feature drift detection.
- Bachelor’s degree in Computer Science, Engineering, or a related field (implied by the level of expertise required).
Benefits & Perks
Salary range of 180,000-240,000
Onsite work schedule 5 days a week
Work environment perks related to a collaborative and inclusive culture
Support for professional growth and development in ML infrastructure, MLOps, and DevOps
Opportunities to work on cutting-edge autonomous vehicle technology
Engagement in innovative projects with industry-leading companies like Walmart
Access to advanced hardware and software tools for AI and infrastructure development
Ready to Apply?
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