What are the responsibilities and job description for the AI/ML Engineering Manager position at CORSAIR?
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
Salary : $170,000 - $210,000