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Lead the build and operation of MLOps platforms on AWS for autonomous-driving ML workloads, using Ray, Kubernetes, Airflow, MLflow, and CI/CD pipelines.
Build generative and predictive ML models to decode cellular behavior and guide drug discovery using single-cell multi-omics and perturbation data.
Senior backend engineer building distributed AI training infrastructure and orchestration services to support scalable model development and experimentation.
Senior engineer building backend systems for AI agent orchestration and distributed training at Lightning AI, the creators of PyTorch Lightning.
Build and scale generative and predictive ML models for cellular behavior using PyTorch and distributed training, bridging research prototypes to production-grade systems in a TechBio company.
Build and optimize large language models for insurance workflows, focusing on post-training, evaluation, and inference performance to improve underwriting and claims processing.
Principal AI/ML Architect designs and advises on production ML systems, MLOps/LLMOps pipelines, and GenAI architectures on AWS for enterprise clients, translating technical depth into business value.
Lead the design and architecture of Stripe’s ML Platform, building scalable systems for training, serving, and monitoring ML models that power fintech products like Payments and Radar.
Lead the design and deployment of AI/ML features for a commercial real estate SaaS platform, including LLM-powered tools and custom domain models, while setting engineering standards and mentoring teams.
Kodiak Robotics, Inc. was founded in 2018 and has become a leader in autonomous ground transportation committed to a safer and more efficient future for all. The company has developed an artificial intelligence (AI)…
Build and deploy large-scale AI foundation models for machine-generated data (logs, graphs, time series) to improve reliability, security, and predictive insights across Splunk’s observability and security platforms.
AI Applications Engineer – Remote Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a…
Optimize AI training and inference workloads for speed, cost, and efficiency across the full stack, from GPU kernels to distributed systems, using Python, C++, and profiling tools.
Define and drive the product strategy for ML training workflows that improve model development speed, training reliability, and developer productivity for GM’s autonomous vehicle platform.
Design and build ultra-low-latency, lossless data-center fabrics for AI training and inference clusters, translating logical topologies into physical deployments across GPU platforms.
Design and deploy deep-learning perception models for automotive ADAS systems, optimizing neural networks for embedded hardware and real-time performance.
Build and scale ML platforms for Reddit’s Ads team, including offline experimentation, training orchestration, and agentic AI workflows to accelerate model development and deployment.
Principal ML Engineer at Grab’s AI Platform team, building and scaling ML infrastructure for Southeast Asia’s superapp, including LLM training/serving, fraud detection, and search ranking.
Build and optimize distributed AI training and inference pipelines for gaming using PyTorch, DeepSpeed, and Kubernetes to support large language models and reinforcement learning workloads.
Build and scale AI infrastructure for industrial automation, bridging research and production with MLOps and distributed systems.
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