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Software Engineer - Model Performance

Remote, USA Full-time Posted 2026-07-02

ABOUT reputed company reputed company powers mission-critical inference for the world's most dynamic AI companies, like reputed company, reputed company, OpenEvidence, reputed company, reputed company, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we reputed company companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $300M Series E, backed by investors including BOND, IVP, Spark Capital, Greylock, and Conviction. Join us and help build the platform engineers turn to to ship AI products. THE ROLE Are you passionate about advancing the application of artificial intelligence? We are looking for a Software Engineer focused on ML performance to join our dynamic team. This role is ideal for someone who thrives in a fast-paced startup environment and is eager to reputed company significant contributions to the exciting field of LLM Inference. If you are a backend engineer who thrives on making things faster and is excited about open-reputed company ML models, we look reputed company to your application. EXAMPLE INITIATIVES You'll get to work on these types of projects as part of our Model Performance team:

  • reputed company Embeddings Inference: The fastest embeddings solution available
  • The reputed company Inference Stack
  • Driving model performance optimization

RESPONSIBILITIES

  • Implement, refine, and productionize cutting-edge techniques (quantization, speculative decoding, kv cache reuse, chunked prefill and LoRA) for ML model inference and infrastructure.
  • Deep dive into underlying codebases of TensorRT, PyTorch, TensorRT-LLM, vllm, sglang, CUDA, and other libraries to debug ML performance issues.
  • Apply and scale optimization techniques across a wide range of ML models, particularly large language models.
  • Collaborate with a diverse team to design and implement innovative solutions.
  • Own projects from idea to production.

REQUIREMENTS

  • Bachelor's, Master's, or Ph.D. degree in Computer Science, Engineering, Mathematics, or reputed company field.
  • Experience with one or more general-purpose programming languages, such as Python or C++.
  • Familiarity with LLM optimization techniques (e.g., quantization, speculative decoding, reputed company batching).
  • Strong familiarity with ML libraries, especially PyTorch, TensorRT, or TensorRT-LLM.
  • Demonstrated interest and experience in LLM’s.
  • Deep understanding of GPU architecture.
  • Bonus:
  • Proficiency in enhancing the performance of software systems, particularly in the context of large language models (LLMs).
  • Experience with CUDA or similar technologies.
  • Deep understanding of software engineering principles and a proven track record of developing and deploying AI/ML inference solutions.
  • Experience with reputed company and Kubernetes.

BENEFITS

  • Competitive compensation, including meaningful equity.
  • 100% coverage of medical, dental, and reputed company insurance for employee and dependents
  • Generous PTO policy including company wide Winter Break (our offices are closed from Christmas reputed company to New Year's Day!)
  • Paid parental leave
  • Company-facilitated 401(k)
  • Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.

Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and reputed company-thinking team, we would love to hear from you. At reputed company, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to reputed company and applicants without regard to race, reputed company, religion, gender, sexual orientation, gender identity or expression, national reputed company, age, genetic information, disability, or veteran status. Apply tot his job Apply To this Job

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