Candidate Profile — Candidate #5
Position: Modular — Engineering Director, GenAI Enterprise (Remote)
Candidate Location: Not specified
Experience: 32.8 years experience

Relevant Experience & Education Highlights

Led AI partner engineering initiatives at a major technology platform, delivering production-scale PyTorch optimizations, customer collaborations, and large model scaling expertise perfectly suited to direct Modular's GenAI Enterprise team.

1. Serve as the primary engineering point of contact for enterprise prospects and customers

Excelled in customer-facing technical roles, solving complex AI challenges alongside cloud providers, ML leaders, and enterprises.

  • Led Applied AI strategic initiatives for PyTorch across cloud service providers and enterprises at a major social media platform.
  • Collaborated on large-scale model training projects including 1T parameter models with major cloud providers.
  • Cultivated relationships through MLOps integrations like PyTorch Kubeflow pipelines and Google Vertex AI.
  • Co-created tools such as TorchServe and Llama-recipes to support enterprise production deployments.

2. Hands-on experience with production AI workloads including scaling and serving large models

Drove optimizations and deployments for large-scale AI training and inference across heterogeneous hardware.

  • Developed model optimizations for large-scale training and inference, featured in publications like MLSys’22 Sustainable AI paper and ASPLOS’24 PyTorch2 Compiler paper.
  • Enabled heterogeneous hardware support including AWS Trainium, Inferentia2, and Google Cloud TPUs with PyTorchXLA.
  • Implemented reproducible AI workflows using PyTorch with MLflow and TorchElastic for scalable training.
  • Supported production settings through PyTorch Enterprise, Profiler, and trainer integrations.

3. 3+ years of management experience with a proven track record of building high-performing collaborative teams

Directed engineering teams in AI research, R&D transformation, and strategic technology initiatives.

  • Spearheaded R&D transformation at a major telecommunications company, adopting Agile, CI/CD, and DevOps to reduce cycle times by 50%.
  • Led AI practice as head at an AI startup and founded technology leadership at a software group.
  • Directed technology strategy and advanced R&D, driving cloud adoption for product portfolio refresh.
  • Managed cross-functional teams for PyTorch ecosystem growth in production environments.

Requirements & Candidate Alignment

Modular RequirementCandidate Qualification
7+ Years of experience in a customer-facing technical roles where you solved hard problems alongside clients32.8 years total experience including leading PyTorch partner engineering for enterprises at a major technology platform
3+ Years of management experience with a proven track record of building high-performing collaborative teamsExtensive management tenure as AI/PyTorch Partner Engineering Head and Director of Technology Strategy at Fortune 500 telecommunications firm
In-depth understanding of the GenAI execution lifecycle, deployment methodologies, along with testing and quality evaluation methodologiesProven GenAI lifecycle expertise through large model optimizations, MLOps pipelines with PyTorch Kubeflow and MLflow, and publications on scaling
Hands-on experience with production AI workloads including scaling and serving large modelsProduction-scale AI leadership scaling 1T parameter models on AWS/GCP, heterogeneous hardware like Trainium/Inferentia2/TPUs with PyTorch
Proficiency in Mojo, Python, C++, or CUDA programming languages, plus familiarity with frameworks such as MAX, Pytorch, or vLLMDeep PyTorch proficiency alongside Python and C++ expertise, co-creating TorchServe and driving PyTorch2 compiler advancements
Proven ability to rapidly prototype and deliver Proofs of Concept (POCs) that win customer confidenceDelivered enterprise POCs via PyTorch Profiler, Enterprise features, and integrations proving value in production settings
Adept at navigating ambiguity and ability to exercise sound judgment to identify appropriate solutions and toolsNavigated complex R&D transformations adopting Agile/DevOps/cloud strategies at telecommunications leader for business growth

If you would like to discuss this candidate or other critical roles, here is a link to my calendar to schedule a call:

Schedule a Call

Contact:

Jason Rath

TalentPros.AI

Finding the signal in the noise since 2005

512-993-8228

Jason@TalentPros.AI

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