Inception
Member of Technical Staff, ML Product Engineering
San Mateo, USA · Staff+
Sponsorship not specifiedDetected 134 days ago
GitAWSGCPAzureCloud PlatformsDockerMachine LearningPyTorchData EngineeringNLPLLMsMLOpsResearchCommunication
About the role
- We seek experienced engineers and scientists to bridge the gap between research and real-world applications by training and deploying our diffusion large language models.
Responsibilities
- Design, develop, and optimize our models for production use cases.
- Implement innovative approaches for post-training generative AI models, including agentic workflows.
- Collaborate with product teams to design and implement customer-facing ML features.
Requirements
- Experience with LLM serving frameworks like vLLM, SGLang, or TensorRT.
- Experience with cloud platforms (AWS, GCP, Azure).
- Experience with model quantization and optimization techniques.
Nice to have
- The Role We seek experienced engineers and scientists to bridge the gap between research and real-world applications by training and deploying our diffusion large language models.
- Work on data preprocessing pipelines, model evaluation, and alignment to enterprise use cases.
- Contribute to the deployment and maintenance of models in production environments.
- At least 5 years of experience working on ML projects in PyTorch (or equivalent), preferably in a research lab or engineering role.
- Experience training LLMs, including fine-tuning.
- Familiarity with large-scale systems and high-performance computing, including GPU/TPU utilization.
- Experience with version control (Git) and containerization (Docker).
- Excellent communication skills with the ability to explain technical concepts to non-technical stakeholders.
Benefits
- Qualifications BS/MS/PhD in Computer Science, Machine Learning, or a related field (or equivalent experience).
- Excellent familiarity with transformers and core LLM concepts (autoregressive pretraining, instruction tuning, in-context learning, LoRA, KV caching).
Company info
- Partner with customers to understand their requirements and translate them into technical solutions.
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This listing is sourced directly from Inception's careers page and normalized into a canonical job model.