Corsair Gaming

AI/ML Director

Milpitas, CA, United States

Open 4 months, first seen by us 134 days ago

Pay: USD 170,000–210,000/yearNot guaranteed — pay source
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
Read the full posting
Work setting: Not stated
Employment: Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting

CORSAIR is building a production-grade AI/ML capability spanning intelligent automation, agentic systems, predictive analytics, and data engineering.

Architect and ship agentic AI systems with orchestration, tool use and evaluation
Build durable automation pipelines with retries using tools like Temporal
Develop and deploy predictive ML models through production monitoring
Build RAG systems, vector retrieval pipelines and prompt strategies
Lead engineers, own delivery standards and the AI/ML technical roadmap

From the employer’s posting

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

Architect agentic AI systems end to end: multi-agent orchestration, tool use, memory management, human-in-the-loop controls, and evaluation frameworks

Build durable, fault-tolerant automation pipelines using workflow orchestration tools such as Temporal

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

Lead and manage a team of engineers and contractors across multiple AI/ML and automation workstreams; own delivery standards, architecture quality, and team development

What you’ll bring

All qualifications

Core experience

6+ years in AI/ML engineering or applied data science, with at least 1-2 years in a technical lead role
Experience in gaming, consumer electronics, or hardware/peripherals
Proven experience designing and deploying agentic AI systems in production: orchestration, tool use, memory, and evaluation
Familiarity with LLM fine-tuning (LoRA, PEFT), vector databases, generative AI for images, or MLOps tooling (MLflow, W&B)
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 working cross-functionally with Product, Finance, Legal, and Operations stakeholders

Qualification wording

6+ years in AI/ML engineering or applied data science, with at least 1-2 years in a technical lead role

Experience in gaming, consumer electronics, or hardware/peripherals

Proven experience designing and deploying agentic AI systems in production: orchestration, tool use, memory, and evaluation

Familiarity with LLM fine-tuning (LoRA, PEFT), vector databases, generative AI for images, or MLOps tooling (MLflow, W&B)

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 working cross-functionally with Product, Finance, Legal, and Operations stakeholders

Apply at Corsair Gaming

Posting record

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Open 4 monthsWe first saw this posting 134 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records: Live
First seen by us: Jun 23, 2026134 days ago
Recorded sightings: 135
Last seen by us: Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$154K–$225K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 2,958 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 134

Up longer than most. Similar jobs usually come down between day 7 and day 53.

From 7,823 similar postings that came down. Coming down is not always a hire.

Corsair Gaming is hiring

2 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Its jobs tend to stay up a long time

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

Python
SQL
AWS
Azure
dbt
Docker
Kubernetes
MLflow
Spark
Airflow
Dagster

Where the posting names them

- 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

- 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

- 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

- 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

- 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

- 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)

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About the role

We file this job under Data Leadership, by the work the posting describes.

Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.

Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.

Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.

US government figures for computer and information systems managers

Median yearly pay, May 2025: $175,140
Expected change, 2025 to 2035: 15.8% more jobsagainst 3.5% for all jobs

The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 11-3021.

Job description

View original posting ↗

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

Source details

View original posting ↗

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Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay

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

Location & working pattern