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Corsair

Develops high-performance gaming and streaming gear

AI/ML Director

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeMilpitas, CA, USA$170k - $210k /yr

About the Job

Requirements

  • At least 6 years of experience in AI/ML engineering or applied data science, including at least 1–2 years in a technical lead role.
  • Proven experience designing and deploying production agentic AI systems, including orchestration, tool use, memory, and evaluation.
  • Strong Python and SQL skills; hands-on experience with LLM frameworks such as LangChain, LangGraph, CrewAI, or Strands, or equivalent, and cloud AI platforms such as AWS Bedrock, Azure AI Foundry, or Microsoft Fabric.
  • Experience with durable workflow orchestration tools such as Temporal, Airflow, or Step Functions.
  • Solid machine learning fundamentals and end-to-end pipeline ownership, with experience using data engineering tools such as dbt, Dagster, and Spark.
  • Demonstrated ability to lead engineers technically and communicate tradeoffs to VP-level stakeholders.

Responsibilities

  • Lead and manage a team of engineers and contractors across multiple AI/ML and automation workstreams; own delivery standards, architecture quality, and team development.
  • Architect end-to-end agentic AI systems, including multi-agent orchestration, tool use, memory management, human-in-the-loop controls, and evaluation frameworks.
  • Own the AI/ML technical roadmap; evaluate build-versus-buy tradeoffs and align with VP-level stakeholders.
  • Engage business stakeholders across functions to map workflows, identify automation opportunities, and translate operational requirements into AI-driven solutions.
  • Design and ship production-grade agentic AI systems using modern LLM orchestration frameworks; own orchestration logic, state management, and output evaluation.
  • Build durable, fault-tolerant automation pipelines using workflow orchestration tools such as Temporal; design for reliability, retry logic, and long-running distributed tasks.
  • Develop and deploy predictive machine learning models; own the full lifecycle from feature engineering through production monitoring.
  • Implement retrieval-augmented generation systems, vector retrieval pipelines, and prompt engineering strategies at scale; apply LLM fine-tuning when it delivers better return on investment than retrieval or prompting.
  • Build and maintain data engineering pipelines using dbt, Dagster, Spark, and Microsoft Fabric; diagnose data quality issues that affect AI system reliability.
  • Own MLOps infrastructure, including experiment tracking, model versioning, retraining pipelines, and drift detection.

Desired Qualifications

  • Experience in gaming, consumer electronics, or hardware/peripherals.
  • Familiarity with LLM fine-tuning methods such as LoRA and PEFT, vector databases, generative AI for images, or MLOps tools such as MLflow and W&B.
  • Exposure to Docker, Kubernetes, and CI/CD pipelines for machine learning workloads.
  • Experience working cross-functionally with Product, Finance, Legal, and Operations stakeholders.

About the Company

Corsair

Develops high-performance gaming and streaming gear

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Company size
1,001-5,000
Company stage
IPO
Headquarters
Milpitas, CA
Founded
1994

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