lever
MLE, ML Platform
Zaimler
San Mateo, USA
Full-time
Mid · 2+ years experience
Onsite
Discovered 1 weeks ago
C++PythonPyTorchTensorFlowHuggingFace TransformersLLMs
Free
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C++PythonPyTorch
Key Skills for This Role
C++PythonPyTorchTensorFlowHuggingFace TransformersLLMs
Full Job Posting
- Develop new algorithms and data structures to improve extraction, tagging and resolution
- Collaborate closely with infra and data engineers to scale your research into production-ready components
- Prototype and refine models for extracting structured knowledge from text
- Apply knowledge distillation techniques to compress and optimize LLMs for downstream tasks
- Explore the use of reinforcement learning and feedback loops for improving model behavior
- Build evaluation pipelines for entity linking, retrieval, and semantic consistency
- Read, implement, and build upon recent research in LLM alignment, distillation, and symbolic grounding
- 2–4 years experience (research lab, internship, academic project, or early industry role) working in ML or NLP
- Strong fundamentals turning research papers, algorithms and mathematics into scalable and robust C++ code
- Solid understanding of ML fundamentals: training pipelines, loss functions, evaluation metrics
- Exposure to knowledge distillation, RLHF, or curriculum learning techniques
- Strong Python skills and familiarity with ML frameworks like PyTorch or TensorFlow
- Experience with language models and transformers (e.g., BERT, LLaMA, or similar)
- A collaborative mindset and willingness to work across research and engineering teams
- Familiarity with reinforcement learning, including policy optimization or reward modeling
- Familiarity with using and scaling algorithms to manipulate data, including graph algorithms, text-manipulation, embeddings.
- Experience with semantic representations such as knowledge graphs or entity embeddings
- Comfort working with tools like HuggingFace Transformers, Ray, or vLLM
- Understanding of small-model techniques (pruning, quantization, adapter layers)
- Interest in the LLM ecosystem and techniques for model alignment or prompt tuning
- Prior contributions to open-source projects or academic publications in ML/NLP
- A rare chance to be a founding engineer shaping both company and product direction.
- Competitive salary, benefits, and meaningful equity.
- Work alongside engineers and researchers from LinkedIn, Visa, Meta, and Branch.
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