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- Tasks: Lead AI engineering for innovative recommender systems and mentor a dynamic team.
- Company: Join a cutting-edge tech company focused on AI solutions.
- Benefits: Comprehensive benefits package, including health insurance and flexible spending accounts.
- Other info: Opportunity to build processes and teams from the ground up in a collaborative environment.
- Why this job: Shape the future of AI technology and make impactful contributions.
- Qualifications: 8-10 years in software systems with strong AI/ML expertise and leadership skills.
The predicted salary is between 80000 - 100000 £ per year.
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.
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, RAG architectures, Cloud software infrastructure experience (AWS/Azure, Databricks, Terraform, Elasticsearch, etc.).
- Communication skills: Ability to explain complex ML concepts to non‑technical stakeholders.
Highly Valued
- 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.
Benefits
Renesas offers a wide range of elective benefits including medical, dental, vision, health savings account, dependent care flexible spending account, pre‑tax commuter benefits, life insurance.
Sr Staff AI Software Development Engineer employer: Renesas Electronics
Contact Detail:
Renesas Electronics Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Sr Staff AI Software Development Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI and software development space. Attend meetups, webinars, or even online forums where you can chat with industry folks. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects or contributions to open-source software. This is your chance to demonstrate your hands-on experience and technical expertise, which is super important for roles like Sr Staff AI Software Development Engineer.
✨Tip Number 3
Prepare for interviews by brushing up on your communication skills. Practice explaining complex ML concepts in simple terms, as you'll need to bridge the gap between technical and non-technical stakeholders. We want you to shine when discussing your vision for AI engineering!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team and contributing to our AI Recommender System engineering function.
We think you need these skills to ace Sr Staff AI Software Development Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of Sr Staff AI Software Development Engineer. Highlight your experience with AI/ML components and any leadership roles you've held. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background makes you the perfect fit for our team. Don’t forget to mention specific projects or achievements that relate to the job.
Showcase Your Technical Skills: In your application, be sure to showcase your technical expertise, especially in areas like MLOps, PyTorch, and cloud infrastructure. We’re looking for someone who can hit the ground running, so let us know what you bring to the table!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get all the updates directly from us. Plus, it’s super easy!
How to prepare for a job interview at Renesas Electronics
✨Know Your AI Stuff
Make sure you brush up on your AI/ML knowledge, especially around recommender systems and the specific technologies mentioned in the job description. Be ready to discuss your experience with fine-tuning models and MLOps, as well as how you've applied these in real-world scenarios.
✨Show Your Leadership Skills
Since this role involves building and managing a team, be prepared to share examples of how you've successfully led teams in the past. Talk about your approach to mentoring and developing talent, and how you've established engineering standards and best practices in previous roles.
✨Bridge the Gap
Highlight your ability to communicate complex ML concepts to non-technical stakeholders. Prepare examples of how you've translated technical jargon into understandable terms for business leaders, showcasing your communication skills and your understanding of both technical and business perspectives.
✨Be Ready for Technical Challenges
Expect to face some technical questions or challenges during the interview. Brush up on your problem-solving skills and be ready to demonstrate your hands-on experience with production ML systems. Think about how you would architect solutions and tackle potential issues that could arise in the role.