AI/ML Engineering Manager

Corsair Gaming, Inc.; Milpitas (CA); On-site; USD 170,000 - 210,000; Full time

Job summary

Corsair Gaming, Inc. seeks an AI/ML Engineering Manager to lead a team building production-grade AI/ML capabilities and automation across the organization. You will stay hands-on as a technical contributor while guiding architecture, strategy, and execution.

You will collaborate with stakeholders to surface automation opportunities, own end-to-end lifecycle, and deliver robust agentic AI systems. The role requires strong Python/SQL, LLM frameworks, and cloud platforms, with a focus on

Qualifications

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

Responsibilities

• Lead a team of engineers and contractors across multiple AI/ML and automation workstreams; own delivery standards, architecture quality, and team development
• Architect agentic AI systems end to end: multi-agent orchestration, tool use, memory management, human-in-the-loop controls, and evaluation frameworks
• Own the AI/ML technical roadmap; evaluate build vs. 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 ML models; own the full lifecycle from feature engineering through production monitoring
• Implement RAG systems, vector retrieval pipelines, and prompt engineering strategies at scale; apply LLM fine-tuning when it delivers better ROI than retrieval or prompting
• Build and maintain data engineering pipelines (dbt, Dagster, Spark, Microsoft Fabric); diagnose data quality issues that affect AI system reliability
• Own MLOps infrastructure: experiment tracking, model versioning, retraining pipelines, and drift detection

Skills

Python

SQL

LLM frameworks

Cloud platforms

Leadership

Tools

Temporal

Airflow

Step Functions

dbt

Dagster

Spark

Kubernetes

Job description

ABOUT THIS ROLE

CORSAIR is building a production-grade AI/ML capability spanning intelligent automation, agentic systems, predictive analytics, and data engineering. As AI/ML Engineering Manager, you will lead a team while staying hands-on as a technical contributor. You will architect and build AI/ML systems that directly affect how the business operates, engage stakeholders across functions to surface automation opportunities, and own the full AI/ML lifecycle end-to-end

WHAT YOU WILL DO

Technical Leadership (40%)

• 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 agentic AI systems end to end: multi-agent orchestration, tool use, memory management, human-in-the-loop controls, and evaluation frameworks
• Own the AI/ML technical roadmap; evaluate build vs. 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

Individual Contribution (60%)

• 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 ML models; own the full lifecycle from feature engineering through production monitoring
• Implement RAG systems, vector retrieval pipelines, and prompt engineering strategies at scale; apply LLM fine-tuning when it delivers better ROI than retrieval or prompting
• Build and maintain data engineering pipelines (dbt, Dagster, Spark, Microsoft Fabric); diagnose data quality issues that affect AI system reliability
• Own MLOps infrastructure: experiment tracking, model versioning, retraining pipelines, and drift detection

WHAT YOU BRING

Required

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

Preferred

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

For roles that are based at our headquarters in Milpitas, CA: The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual salary could fall outside of this expected range. This pay range is subject to change and may be modified in the future.

Annual Salary Range $170,000—$210,000 USD