Improve the performance of Hark's Megatron-based pretraining systems across thousands of GPUs, focusing on model FLOPs utilization, training throughput, and kernel performance.
Compensation
The US base salary range for this full-time position is between $180,000 - $450,000 annually.
Responsibilities
Own MFU and step time for pretraining runs across dense and mixture-of-experts models
Write or integrate fused and custom kernels (CUDA, Triton, CUTLASS) for attention, normalization, and mixture-of-experts routing
Overlap communication with compute, reduce pipeline bubbles, and tune activation recomputation and memory use to raise throughput per GPU
Implement model and optimizer sharding, and optimize data, tensor, pipeline, sequence, context, and expert parallelism for dense and mixture-of-experts architectures
Profile GPU kernels, collective communication, data loading, and mixed-precision training to identify performance and numerical stability bottlenecks
Requirements
Nice to have: mixture-of-experts training at scale
Nice to have: load balancing
Nice to have: all-to-all communication optimization
Develop and curate multimodal datasets for pretraining Hark's AI models, focusing on text, code, image, and video modalities, and design training mixtures and experiments to improve model performance.
Compensation
The US base salary range for this full-time position is between $180,000 - $450,000 annually.
Responsibilities
Develop methods to select, filter, deduplicate, and prepare text, code, image, and video datasets at scale.
Build paired and interleaved datasets, including image-text documents and video-text data.
Build quality classifiers and sampling methods, and measure their impact through controlled training experiments.
Develop synthetic captioning and other supervision methods for image and video data, and assess their accuracy, coverage, and biases.
Design mixtures and curricula across sources, domains, and modalities.
Build and maintain evaluation harnesses for multimodal foundation models, design and analyze benchmarks, and collaborate with researchers to improve training recipes and capability assessments.
Compensation
The US base salary range for this full-time position is between $180,000 - $450,000 annually.
Responsibilities
Build and maintain an evaluation harness for held-out loss, performance across data domains, and capabilities in text, code, math, and reasoning.
Design evaluations for early checkpoints and smaller models using log-likelihood scoring, few-shot prompts, and generated completions.
Assess benchmark coverage and saturation, quantify uncertainty in results, and work with data researchers to detect training-data contamination.
Version datasets, prompts, graders, and inference settings so results can be reproduced and compared across checkpoints and training runs.
Analyze experiments and work with researchers to identify useful recipe changes, select checkpoints, and prioritize capability improvements.
The AI Enablement Engineer is responsible for designing and scaling enterprise-grade AI solutions that enhance productivity and automate workflows across the firm. This role focuses on leveraging Microsoft Copilot, Azure AI Foundry, and Anthropic Claude ecosystem (Claude, Claude Code, Agents, CoWork) to build agentic AI capabilities.
Responsibilities
Design and implement AI-driven solutions using Copilot Studio, Azure AI Foundry, and Claude ecosystem tools
Build and deploy agentic workflows and intelligent agents
Develop integrations across enterprise systems using APIs and AI platforms
Leverage AI to process documents and automate decision workflows
Align solutions with Azure AI Foundry-based architecture
Senior Data Scientist in the Risk Based Quality Management (RBQM) Analytics team, responsible for advanced analytics, machine learning, and visual analytics to support clinical development.
Responsibilities
Connects with cross-functional teams to design work product and act as an analytics consultant
Anticipates and identifies issues that could affect timelines or quality and develops options and solutions
Leads and helps establish design principles and standards to ensure analytical work product consistency
Develops prototypes, test methods and algorithms using emerging statistical methodologies, ML and AI
Enables data-driven insights to support clinical development continuum, including precision medicine
Requirements
Bachelor’s degree in statistics, analytics, bioinformatics, data science or equivalent field
The Senior Data Scientist role is a key role to enable application of advanced analytics techniques across clinical development continuum. Drives Analytics innovation and experimentation to enable data-driven insights for complex business problems across R&D.
Responsibilities
Connects with cross-functional teams to design work product and as an analytics consultant.
Anticipates and identifies issues that could affect timelines or quality and develops options and solutions.
Leads and helps establish the design principles and standards to ensure analytical work product is consistent across projects and that user experience is optimized.
Develops prototypes, test methods and algorithms.
Leverages emerging statistical methodologies, ML and AI to drive innovative analytical solutions to create insights.
Lead technical projects and programs, integrating software and hardware for customer deployments, managing end-to-end deployment, training, and special projects.
Compensation
Under California’s Pay Transparency Act (SB 1162), the expected base salary range for this position in Sunnyvale, CA is $150,000 – $210,000 per year.
Responsibilities
Deployments
Site readiness
Integration
Test and evidence
Sim-to-real
Requirements
BS or MS in Mechanical, Electrical, Computer, or Robotics Engineering, Computer Science, or equivalent
Nice to have: Deployments in logistics, warehousing, or trailer loading/unloading
Nice to have: heavy industry experience
Nice to have: humanoid or whole-body control experience
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