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AI & Machine Learning
Staff ML Engineer - LLM Infrastructure
About the Role
We're building the next generation of talent-matching technology powered by large language models. As a Staff ML Engineer, you'll architect and scale our LLM infrastructure that processes thousands of engineer profiles and job requirements daily.
You'll work on challenging problems: semantic understanding of technical skills, multi-modal resume parsing, real-time matching algorithms, and building evaluation frameworks that ensure our 98% placement success rate.
This role is for you if:
- You've deployed LLMs to production and understand the trade-offs between model size, latency, and cost
- You're excited about RAG architectures, fine-tuning, and prompt engineering at scale
- You believe in measuring everything and letting data drive decisions
- You want to work on a product that directly impacts how companies build engineering teams
What You'll Do
- Design and implement our LLM-powered skill extraction and matching pipeline
- Build and maintain RAG systems for contextual understanding of engineer profiles
- Develop evaluation frameworks to measure and improve model performance
- Optimize inference latency and cost for real-time matching (target: <200ms p99)
- Lead technical design reviews and establish ML engineering best practices
- Collaborate with product to translate business requirements into ML solutions
- Mentor mid-level engineers and contribute to hiring decisions
- Stay current with ML research and evaluate new techniques for our use cases
What We're Looking For
- 8+ years of software engineering experience, with 4+ years focused on ML/AI
- Production experience with LLMs (GPT-4, Claude, Llama, etc.) including fine-tuning and RAG implementations
- Deep expertise in Python, PyTorch or TensorFlow, and ML infrastructure (MLflow, Weights & Biases, etc.)
- Experience with vector databases (Pinecone, Weaviate, Milvus) and embedding models
- Strong understanding of transformer architectures and attention mechanisms
- Track record of leading technical projects and mentoring engineers
- Experience with distributed training and model optimization (quantization, distillation)
- Excellent written communication - you document your work and explain complex concepts clearly
What We Offer
- Base salary: $220,000 - $280,000 depending on experience
- Equity package: 0.15% - 0.3% with 4-year vesting
- Fully remote with $5,000 home office budget
- Unlimited PTO (minimum 4 weeks required)
- Premium health, dental, vision for you and dependents
- $5,000 annual learning budget (conferences, courses, books)
- Latest MacBook Pro or Linux workstation of your choice
- Annual team offsite in interesting locations
Apply for this Position
Submit your application below. We'll review it within 48 hours and get back to you.