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ML Research & Engineering Engineer
About TensorZero: TensorZero is an open-source stack for industrial-grade LLM applications, unifying gateway, observability, optimization, evaluations, and experimentation. We’re seeking an ML Research & Engineering Engineer to join our technical-first team, where you’ll develop and implement machine learning algorithms for our platform.
Key Responsibilities:
- Design and implement machine learning models for optimization and evaluation
- Collaborate with researchers to advance TensorZero’s ML capabilities
- Develop algorithms for inference-time optimization and evaluation
- Build tools for model fine-tuning and experimentation
- Analyze performance metrics and improve model efficiency
- Contribute to open-source ML research projects
Required Skills:
- Strong background in machine learning and AI
- Experience with Python, PyTorch, or TensorFlow
- Knowledge of optimization techniques (RLHF, fine-tuning)
- Familiarity with large language models and their applications
- Experience with experimentation and A/B testing frameworks
- Excellent analytical and problem-solving skills
Ideal Candidate: An ML engineer with 4+ years of experience in machine learning research and application. You should have a strong publication record or industry experience with large-scale ML systems. Experience with LLM optimization and evaluation is highly valued. This role offers the opportunity to work with a small, collaborative team on cutting-edge AI research with significant impact on TensorZero’s product direction.
About the Company: TensorZero provides an open-source platform for industrial-grade LLM applications, enabling developers to build, deploy, and manage LLM applications with ease. We’re backed by reputable investors and have raised $7.2M in seed funding. Our team includes experts from top institutions and industry leaders, creating a collaborative environment focused on innovation and growth.
Compensation: The estimated pay range for this role is $180,000 - $240,000, with equity options as part of our compensation package.