Machine Learning Engineer - Inference

Posted 5 Days Ago
San Francisco, CA
Mid level
Artificial Intelligence • Information Technology
The Role
The Machine Learning Engineer will optimize AI inference systems, develop runtime inference services, and collaborate with teams to enhance AI capabilities. Responsibilities include designing production systems, conducting code reviews, and implementing robust data processing systems.
Summary Generated by Built In


Role

Together AI is seeking a Machine Learning Engineer to join our Inference Engine team, focusing on optimizing and enhancing the performance of our AI inference systems. This role involves working with state-of-the-art large language models models and ensuring they run efficiently and effectively at scale. If you are passionate about AI inference, PyTorch, and developing high-performance systems, we want to hear from you. This position offers the chance to collaborate closely with AI researchers and engineers to create cutting-edge AI solutions. Join us in shaping the future at Together AI!

Responsibilities

  • Design and build the production systems that power the Together AI inference engine, enabling reliability and performance at scale.
  • Develop and optimize runtime inference services for large-scale AI applications.
  • Collaborate with researchers, engineers, product managers, and designers to bring new features and research capabilities to the world.
  • Conduct design and code reviews to ensure high standards of quality.
  • Create services, tools, and developer documentation to support the inference engine.
  • Implement robust and fault-tolerant systems for data ingestion and processing.

Requirements

  • 3+ years of experience writing high-performance, well-tested, production-quality code.
  • Proficiency with Python and PyTorch.
  • Demonstrated experience in building high performance libraries and tooling.
  • Excellent understanding of low-level operating systems concepts including multi-threading, memory management, networking, storage, performance, and scale.
  • Preferred: Knowledge of existing AI inference systems such as TGI, vLLM, TensorRT-LLM, Optimum
  • Preferred: Knowledge of AI inference techniques such as speculative decoding.
  • Preferred: Knowledge of CUDA/Triton programming.
  • Nice to have: Knowledge of Rust, Cython and compilers.

About Together AI

Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society. Together, we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI. Our team has been behind technological advancements such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey to build the next-generation AI infrastructure.

Compensation

We offer competitive compensation, startup equity, health insurance, and other competitive benefits. The US base salary range for this full-time position is $160,000 - $230,000 + equity + benefits. Our salary ranges are determined by location, level, and role. Individual compensation will be determined by experience, skills, and job-related knowledge.

Equal Opportunity

Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunities to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.


Top Skills

Python
PyTorch
The Company
San Francisco, California
84 Employees
On-site Workplace
Year Founded: 2022

What We Do

Together AI is a research-driven artificial intelligence company. We contribute leading open-source research, models, and datasets to advance the frontier of AI. Our decentralized cloud services empower developers and researchers at organizations of all sizes to train, fine-tune, and deploy generative AI models. We believe open and transparent AI systems will drive innovation and create the best outcomes for society

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