The LLM Algorithm Engineer will advance post-training of large language models, manage context protocols, optimize distributed training, and build evaluation pipelines.
Job Responsibilities：
1. Advanced post-training of large language models (e.g. SFT, RLHF/RLAIF, continual pretraining).
2. Aligning models for reliable JSON-schema function calls and external tool usage.
3. Design, deploy, and operate Model Context Protocol (MCP) servers that handle checkpoint routing, manage context windows, and enforce safety gates.
4. Experience in distributed training and inference with DeepSpeed/FSDP, LoRA/QLoRA, mixed precision, and performance tuning on vLLM or Triton clusters.
5. Build offline and live eval pipelines for alignment, factuality, grounding, and hallucinations.
Qualifications
1. Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
2. 3+ years of experience in developing and optimizing large language models.
3. Proven track record in implementing advanced post-training techniques (SFT, RLHF, RLAIF, continual pretraining).
4. Hands-on experience with distributed training frameworks (DeepSpeed, FSDP) and optimization techniques (LoRA, QLoRA, mixed precision).
5. Familiarity with model alignment, JSON-schema function calls, and external tool integration.
6. Experience in building and maintaining evaluation pipelines for model performance assessment.
7. Proficiency in Python and relevant machine learning frameworks (e.g., PyTorch, TensorFlow).
8. Strong understanding of distributed systems and high-performance computing.
9. Experience with model deployment and inference optimization on vLLM or Triton clusters.
10. Knowledge of JSON-schema and API development.
Top Skills
Deepspeed
Fsdp
Lora
Python
PyTorch
Qlora
TensorFlow
Triton
Vllm
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Home to tech titans like Microsoft and Amazon, Seattle punches far above its weight in innovation. But its surrounding mountains, sprinkled with world-famous hiking trails and climbing routes, make the city a destination for outdoorsy types as well. Established as a logging town before shifting to shipbuilding and logistics, the Emerald City is now known for its contributions to aerospace, software, biotech and cloud computing. And its status as a thriving tech ecosystem is attracting out-of-town companies looking to establish new tech and engineering hubs.
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- Number of Tech Workers: 287,000; 13% of overall workforce (2024 CompTIA survey)
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- Funding Landscape: $3.1 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Madrona, Fuse, Tola, Maveron
- Research Centers and Universities: University of Washington, Seattle University, Seattle Pacific University, Allen Institute for Brain Science, Bill & Melinda Gates Foundation, Seattle Children’s Research Institute
