At a Glance
- Tasks: Build scalable AI data pipelines and manage data ingestion on GCP.
- Company: Join Speechify, a cutting-edge AI company in Cambridge.
- Benefits: Enjoy competitive pay, flexible work options, and growth opportunities.
- Other info: Collaborate with top scientists in a dynamic and innovative environment.
- Why this job: Make an impact by supporting AI model training with high-quality datasets.
- Qualifications: Experience in data engineering and cloud technologies is a plus.
The predicted salary is between 60000 - 80000 £ per year.
Speechify, located in Cambridge, is seeking a skilled Software Engineer to join our AI team's data division. This role involves data collection to support model training operations, building high-quality datasets at petabyte scale.
You will collaborate closely with scientists and leadership to craft the dataset roadmap, manage the ingestion pipeline on GCP using Terraform, and ensure efficient data sourcing and integration.
Data Infrastructure Engineer for Scalable AI Data Pipelines in Cambridge employer: Speechify
At Speechify, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of Cambridge. Our commitment to employee growth is evident through continuous learning opportunities and the chance to work alongside leading experts in AI, making this role not just a job, but a meaningful career path in a cutting-edge field.
StudySmarter Expert Advice🤫
We think this is how you could land Data Infrastructure Engineer for Scalable AI Data Pipelines in Cambridge
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and data engineering space on LinkedIn or at local meetups. We can’t stress enough how personal connections can open doors for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving data pipelines or GCP. We love seeing real-world applications of your expertise!
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. We recommend practising common interview questions related to data infrastructure and AI to boost your confidence.
✨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, we love candidates who take that extra step!
We think you need these skills to ace Data Infrastructure Engineer for Scalable AI Data Pipelines in Cambridge
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights relevant experience in data infrastructure and AI. We want to see how your skills align with the role, so don’t be shy about showcasing your past projects and achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re excited about the Data Infrastructure Engineer role and how you can contribute to our team at Speechify. Keep it engaging and personal!
Showcase Your Technical Skills:Since this role involves working with GCP and Terraform, make sure to mention any relevant technical skills or projects. We love seeing practical examples of how you've used these tools in your previous work.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Speechify
✨Know Your Data Pipelines
Make sure you understand the ins and outs of data pipelines, especially in the context of scalable AI. Brush up on your knowledge of GCP and Terraform, as these will likely come up during the interview. Be ready to discuss how you've managed data ingestion processes in the past.
✨Showcase Your Collaboration Skills
Since this role involves working closely with scientists and leadership, be prepared to share examples of how you've successfully collaborated in previous projects. Highlight your communication skills and how you’ve contributed to crafting a roadmap for data initiatives.
✨Prepare for Technical Questions
Expect technical questions that test your understanding of data collection and dataset quality. Review common challenges faced when building datasets at petabyte scale and think about how you would address them. Practising coding problems related to data engineering can also give you an edge.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions that show your interest in the role and the company. Inquire about the current challenges the team faces with data sourcing and integration, or how they envision the future of their AI data pipelines. This shows you’re not just interested in the job, but also in contributing to their success.
