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Sr staff ai software development engineer

Cambridge
Renesas Electronics
Development engineer
Posted: 13h ago
Offer description

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

1. Own the recommender AI engineering function: Define technical strategy, architecture, and roadmap based upon functional requirements set by product manager.
2. Build and manage the team: Recruit, onboard, and develop AI engineers; establish team structure, processes, and best practices
3. Establish engineering standards: Create workflows, code review processes, testing frameworks, and documentation practices for ML/AI systems
4. Bridge the gap: Translate between ML engineering and business stakeholders; educate leadership on AI capabilities and limitations
5. Hands-on technical leadership: Architect and build production ML systems while mentoring team members

Qualifications

Required Qualifications

6. 8-10 years in production-grade software systems, building and leveraging AI/ML components in related areas. with significant technical and people management experience
7. PhD or Masters in AI/ML or adjacent field
8. Proven ability to establish AI engineering practices in organizations without core AI/ML expertise
9. Self-directed and autonomous: Comfortable operating with ambiguity and building structure from the ground up
10. AI/ML technical expertise:Fine-tuning foundation LLM and related models (SFT, RLHF, DPO, etc.)MLOps and production ML infrastructurePyTorch, HuggingFace Transformers ecosystemVector databases, RAG architectures
11. Cloud software infrastructure experience (AWS/Azure, Databricks, Terraform, Elasticsearch, etc.)
12. Communication skills: Ability to explain complex ML concepts to non-technical stakeholders

Highly Valued

13. Domain expertise in circuit diagrams, PCB schematics, or electronic engineering
14. Knowledge of Graph Neural Networks (GNN) concepts.
15. Track record of creating engineering processes and teams from scratch

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