Renesas Electronics
Tech / AI / Software
SrStaffAISoftwareDevelopmentEngineer
Neural analysis suggests this role is
optimal for mid candidates.
“Sr Staff AI Software Development Engineer at Renesas Electronics. Skills: AI Recommender System engineering, AI agent systems, production ML systems, MLOps, LLM fine-tuning. Drive AI Recommender System engineering function. Take responsibility for the recommender panel and related functions within cloud-based electronic system design (ESD) tools”
What You'll Achieve.
Make live, context-aware recommendations for documentation links and/or suggestions completing partial user entries; Make a real impact by developing innovative products and solutions to meet our global customers' evolving needs and help make people’s lives easier, safe and secure.
Industry & Context.
dual-use technology that is subject to U.S. export controls regulations
What They're Looking For.
Must Have
8-10 years in production-grade software systems, building and leveraging AI/ML components in related areas., significant technical and people management experience, PhD or Masters in AI/ML or adjacent field, Proven ability to establish AI engineering practices in organizations without core AI/ML expertise, Self-directed and autonomous: Comfortable operating with ambiguity and building structure from the ground up, AI/ML technical expertise, Fine-tuning foundation LLM and related models (SFT, RLHF, DPO, etc. ), MLOps and production ML infrastructure, PyTorch, HuggingFace Transformers ecosystem, Vector databases, RAG architectures, Cloud software infrastructure experience(AWS/Azure, Databricks, Terraform, Elasticsearch, etc. ), Communication skills: Ability to explain complex ML concepts to non-technical stakeholders
Nice to Have
Domain expertise in circuit diagrams, PCB schematics, or electronic engineering, Knowledge of Graph Neural Networks (GNN) concepts., Track record of creating engineering processes and teams from scratch
What You'll Do.
Drive AI Recommender System engineering function
Take responsibility for the recommender panel and related functions within cloud-based electronic system design (ESD) tools
Build upon existing team
Set technical direction
Define technical strategy
and roadmap based upon functional requirements
Establish team structure
code review processes
and documentation practices for ML/AI systems
Translate between ML engineering and business
Educate leadership on AI capabilities and limitations
Architect and build production ML systems
How You'll Work.
Team & Collaboration
Build and manage the team; Bridge the gap between ML engineering and business; Educate leadership on AI capabilities and limitations; Mentor team members
Communication Scope
Ability to explain complex ML concepts to non-technical stakeholders
Process & Methodology
Define technical strategy, architecture, and roadmap, Establish team structure, processes, and best practices, Create workflows, code review processes, testing frameworks, and documentation practices
Full Job Description
Senior Staff AI Software Engineer About the Role: We are seeking an experienced technical leader who can drive our AI Recommender System engineering function. This individual should bring significant experience in AI agent systems embedded within software tools for making live, context-aware recommendations for documentation links and/or suggestions completing partial user entries. The successful candidate will take responsibility for the recommender panel and related functions within our cloud-based electronic system design (ESD) tools. They will build upon our existing small team, define processes, and set technical direction. What You'll Do * Own the recommender AI engineering function : Define technical strategy, architecture, and roadmap based upon functional requirements set by product manager. * Build and manage the team : Recruit, onboard, and develop AI engineers; establish team structure, processes, and best practices * Establish engineering standards : Create workflows, code review processes, testing frameworks, and documentation practices for ML/AI systems * Bridge the gap : Translate between ML engineering and business stakeholders; educate leadership on AI capabilities and limitations * Hands-on technical leadership : Architect and build production ML systems while mentoring team members ## Qualifications Required Qualifications * 8-10 years in production-grade software systems, building and leveraging AI/ML components in related areas. with significant technical and people management experience * PhD or Masters in AI/ML or adjacent field * Proven ability to establish AI engineering practices in organizations without core AI/ML expertise * Self-directed and autonomous : Comfortable operating with ambiguity and building structure from the ground up * AI/ML technical expertise : * Fine-tuning foundation LLM and related models (SFT, RLHF, DPO, etc.) * MLOps and production ML infrastructure * PyTorch, HuggingFace Transformers ecosystem * Vector databases,
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