Job description

About the 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, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month. Compensation We offer competitive compensation, startup equity, health insurance, and other competitive benefits. The US base salary range for this full-time position is $200,000 - $300,000 + 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. Please see our privacy policy at together.ai

Requirements

Must-haves

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.
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.

Nice-to-haves

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.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningpythonllmrust

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Health Insurance