Build and operate production machine learning training systems on Amazon SageMaker using AWS Trainium. The role focuses on optimizing PyTorch code for Trainium hardware, understanding NeuronCore compilation, diagnosing device-level issues, tuning distributed training for cost and throughput, and delivering production pipelines. The engineer will collaborate directly with client and internal teams in a forward-deployed engineering environment.
Robots & Pencils is an AWS Partner building production AI systems for enterprise clients who need real engineering, not proofs of concept that never ship. We work forward-deployed, embedded directly with client teams, solving the problems that are too new or too specialized for a typical vendor relationship to handle.
The Role
We're looking for an engineer who can operate and train models on Amazon SageMaker running on AWS Trainium, AWS's custom silicon built specifically for large-scale model training. This isn't a role where you call an API and wait. You'll be walking up the stack: understanding what a training request actually looks like at the Trainium hardware and compiler level, then carrying that understanding all the way up through PyTorch training code and into a production SageMaker pipeline.
PyTorch is the backbone of this work. If you know the framework deeply and you're comfortable reasoning about how your code actually behaves on custom accelerator hardware rather than treating it as a black box, this role is built around that skill set specifically.
What You'll Do
- Train and operate models on Amazon SageMaker with AWS Trainium as the underlying compute
- Write and optimize PyTorch training code with a real understanding of how it compiles and executes on Trainium (NeuronCore architecture, compiler behavior, memory and throughput tradeoffs)
- Diagnose training run issues that show up specifically because of the hardware, not just the model, distinguishing a data or code problem from a compiler or device-level one
- Translate a request for "a Trainium job" into an actual working, cost-aware training pipeline, end to end
- Tune distributed training runs for throughput and cost on SageMaker's training infrastructure
- Work directly with client and internal engineering teams to scope and deliver real production training workloads, not experiments that stay in a notebook
What You'll Bring
- Strong, hands-on PyTorch experience, ideally including distributed or multi-device training
- Production experience with Amazon SageMaker for training and/or inference
- Comfort working close to the hardware layer: you understand device-specific compilation and can debug issues that are actually about the accelerator, not just the model
- AWS Trainium or Inferentia (Neuron SDK) experience is a strong plus; if you don't have it yet but have deep PyTorch and a track record of picking up new hardware targets fast, we want to talk to you
- Solid Python fundamentals and comfort operating in a client-facing, production engineering environment
Similar Jobs
Artificial Intelligence • Big Data • Healthtech • Machine Learning • Analytics • Biotech • Generative AI
Supports molecular R&D diagnostic assay development by preparing, editing, compiling, filing, and maintaining validation protocols, reports, SOPs, batch records, and work instructions. Ensures documentation consistency, compliance, version control, and audit readiness for IVD and LDT projects. Collaborates with scientists, technologists, quality, and regulatory teams while managing documentation retrieval and continuous process improvements.
Top Skills:
Fda QsmrIso 13485IvdLdtQms
Artificial Intelligence • Cloud • Information Technology • Machine Learning • Natural Language Processing • Software
Own end-to-end localization operations for enterprise clients, serving as the primary operational contact and trusted advisor. Coordinate stakeholders and cross-functional teams, manage localization workflows and configurations across TMS and project tools, resolve client and internal issues, and improve processes through documentation, automation, and AI-enabled solutions. The role requires localization or translation project management experience, client communication skills, familiarity with localization formats and CAT/TMS tools, and strong organizational abilities.
Top Skills:
Ai ToolingAsanaAutomationCat ToolsGoogle SheetsJIRALookerMemoqPhraseSmartlingTranslation Management Systems (Tms)Xtm
Artificial Intelligence • Cloud • Information Technology • Machine Learning • Natural Language Processing • Software
Manage full-cycle talent acquisition, including candidate screening, assessment calls, communication, sourcing, pipeline development, recruiting platform management, and applicant tracking data. Partner with hiring managers to meet hiring goals while delivering an excellent candidate experience and strengthening the employer brand. The role requires proactive outreach, strong organization, relationship-building, adaptability, and effective remote collaboration.
Top Skills:
Applicant Tracking SystemsE-Verify
What you need to know about the Los Angeles Tech Scene
Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.
Key Facts About Los Angeles Tech
- Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
- Key Industries: Artificial intelligence, adtech, media, software, game development
- Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
- Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering
