Performance engineer

writer.com; San Francisco (CA); On-site; USD 150,000 - 200,000; Full time

Job summary

Writer seeks a Principal Performance Engineer to lead performance optimization in their Generative AI technology stack. The role involves critical tasks to enhance efficiency and scalability, collaborating with various teams to deliver top-notch AI solutions. Ideal candidates have extensive experience in performance engineering, particularly within AI-related frameworks and systems.

Benefits

Generous PTO plus company holidays

Medical, dental, and vision coverage

Paid parental leave (12 weeks)

Fertility and family planning support

Flexible spending account options

Health savings account with company contribution

Annual work-life stipends for home office and wellness

Company-wide and team off-sites

Competitive compensation and stock options

Qualifications

• 10+ years in performance engineering, focusing on large-scale distributed systems.
• Experience with AI/ML technologies for 2+ years.
• Familiarity with performance analysis tools.

Responsibilities

• Define performance engineering strategies for AI.
• Lead testing and analysis to identify bottlenecks.
• Collaborate with teams to ensure performance requirements are met.

Skills

Analytical skills

Problem-solving

Communication

Collaboration

Education

Bachelor's degree in Computer Science or Engineering

Master's preferred

Tools

AWS

Azure

GCP

Docker

Kubernetes

Postgres

Elasticsearch

Job description

About this role
Writer is seeking a highly skilled and motivated Principal performance engineer to lead the performance optimization of our cutting-edge Generative AI technology stack. This role is critical in ensuring the scalability, efficiency, and reliability of our Large Language Models (LLMs) and Retrieval Augmented Generation (RAG) systems. You will be a key driver in identifying and resolving performance bottlenecks, optimizing resource utilization, and ensuring a seamless user experience. You will work closely with our AI research, software engineering, and infrastructure teams to deliver world-class AI solutions.

????️ Your responsibilities

• Performance leadership:

  • Define and implement performance engineering strategies for our Generative AI full stack, including services, application, LLMs, RAG pipelines, and related infrastructure.

  • Lead performance testing, profiling, and analysis efforts to identify and resolve performance bottlenecks.

  • Establish and maintain performance benchmarks and SLAs for critical AI services.

  • Provide technical leadership and mentorship to performance engineering team members.

• LLM capacity and tuning:

  • Analyze and improve LLM inference performance, including latency, throughput, and resource utilization.

  • Develop and implement strategies for LLM capacity planning and scaling.

  • Collaborate with AI researchers to evaluate and improve LLM model architectures and training techniques for performance.

  • Optimize LLM inference through techniques such as quantization, distillation, and optimized kernel implementation.

• RAG performance optimization:

  • Design and implement performance tests for RAG pipelines, including retrieval, ranking, and generation components.

  • Identify and optimize performance bottlenecks in RAG systems, such as database queries, vector search, and document processing.

  • Evaluate and optimize RAG system architectures for scalability and efficiency.

  • Tune vector databases for optimal recall and latency.

• Infrastructure optimization:

  • Collaborate with infrastructure teams to optimize hardware and software configurations for AI workloads.

  • Evaluate and recommend new technologies and tools for performance monitoring and analysis.

  • Develop and maintain performance dashboards and reports to track key metrics.

  • Optimize GPU utilization and memory management for LLM inference.

• Collaboration and communication:

  • Work closely with AI researchers, software engineers, and product managers to ensure performance requirements are met.

  • Communicate performance findings and recommendations to stakeholders at all levels.

  • Stay up-to-date with the latest developments in Generative AI and performance engineering.

️ Is this you?

• Education:

  • Bachelor's degree in Computer Science, Engineering, or a related field (Master's preferred).

• Experience:

  • 10+ years of experience in performance engineering, with a focus on large-scale distributed systems.

  • 2+ years of experience working with AI/ML technologies

  • Proven experience in performance testing, profiling, and analysis of complex software systems.

  • Deep understanding of NLP architectures, training, and inference.

  • Experience with vector databases and search technologies.

  • Experience with cloud computing platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).

  • Strong programming skills in python.

  • Familiarity with Postgres and Elasticsearch

  • Experience with performance analysis tools (e.g., profilers, debuggers, monitoring tools).

• Skills:

  • Strong analytical and problem-solving skills.

  • Excellent communication and collaboration skills.

  • Ability to work in a fast-paced and dynamic environment.

  • Passion for AI and a desire to push the boundaries of performance engineering

    #LI-Remote

Benefits & perks (US Full-time employees)

• Generous PTO, plus company holidays

• Medical, dental, and vision coverage for you and your family

• Paid parental leave for all parents (12 weeks)

• Fertility and family planning support

• Early-detection cancer testing through Galleri

• Flexible spending account and dependent FSA options

• Health savings account for eligible plans with company contribution

• Annual work-life stipends for:

  • Home office setup, cell phone, internet

  • Wellness stipend for gym, massage/chiropractor, personal training, etc.

  • Learning and development stipend

• Company-wide off-sites and team off-sites

• Competitive compensation, company stock options and 401k

Writer is an equal-opportunity employer and is committed to diversity. We don't make hiring or employment decisions based on race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other basis protected by applicable local, state or federal law. Under the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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