Senior/Lead MLOps Engineer
The project is in the Explore (Discovery) phase of ATLAS (VLAOps), a Greenfield initiative to develop a Visual-Language-Action ecosystem for autonomous mining and construction vehicles. The objective is to design an end-to-end MLOps toolchain that manages the full lifecycle of foundation world models, from data ingestion and training to simulation and inference. The initial pilot focuses on a Stockpile Management workflow. During this 8-week phase, the engineer will deliver an end-to-end MLOps platform blueprint, a simulation integration strategy, and a design for ultra-low latency edge inference.
Essential functions
E2E & Environment Design
Simulation Integration Strategy
Pipeline Design Strategy
Qualifications
This role focuses on infrastructure and orchestration, not just model tuning.
Deep knowledge of Kubernetes and Ray for distributed training of large models.
MLOps Frameworks: Kubeflow, MLflow, Feature Stores.
Integration with NVIDIA Omniverse, Isaac Sim, or Carla Sim is a critical component of the architecture.
Architecture for Edge AI deployment requiring ultra-low latency (targeting ~30ms decision loops) on resource-constrained hardware.
Cloud: AWS (with Hybrid Federated Architecture concepts).
Would be a plus
Proven experience with "Sim-to-Real" transfer workflows or synthetic data generation using physics engines (Omniverse/Isaac Sim).
Familiarity with ROS (Robot Operating System) nodes or autonomous vehicle stacks.
Experience building training pipelines specifically for Vision-Language-Action (VLA) models or Large Behavioral Models.
Experience designing drift detection and feedback loops for models deployed in physical environments.
We offer
Work on bleeding-edge projects on a team of experienced engineers
Flexible working hours
Specialization courses
24 days annual leave + an additional of 5 sick days
Floating Holidays
Private medical subscription for employees
Benefits basket with the total value of 650 euro net/year
About us
Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.Apply to the position
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