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- Tasks: Manage data lifecycle and enhance model performance with quality datasets.
- Company: Leading AI video company focused on innovation and collaboration.
- Benefits: Competitive compensation, hybrid work flexibility, and growth opportunities.
- Why this job: Join a dynamic team and make an impact in the AI field.
- Qualifications: Strong background in Machine Learning and excellent Python skills.
- Other info: Collaborative environment with a focus on human-centric data solutions.
The predicted salary is between 36000 - 60000 £ per year.
A leading AI video company is seeking a Data Specialist to manage the lifecycle of data for researchers, enhancing model performance through quality datasets. The role involves building a human-centric data lake in collaboration with model training teams.
Candidates should have a strong background in applied Machine Learning, excellent Python skills, and hands-on experience with data quality and workflow orchestration systems.
This position offers competitive compensation and the flexibility of a hybrid work setting.
Senior Data-Driven Research Engineer — ML Data & Pipelines employer: Synthesia
Contact Detail:
Synthesia Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data-Driven Research Engineer — ML Data & Pipelines
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and data space on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can get your foot in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to data quality and machine learning. We want to see your hands-on experience, so make sure to highlight any cool datasets or pipelines you've worked with.
✨Tip Number 3
Prepare for those interviews! Brush up on your Python skills and be ready to discuss your approach to building data lakes and ensuring data quality. We recommend practising common ML scenarios and how you’d tackle them.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Senior Data-Driven Research Engineer — ML Data & Pipelines
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with applied Machine Learning and Python in your application. We want to see how your skills can enhance our data lifecycle and model performance!
Tailor Your Application: Don’t just send a generic CV! Tailor your application to reflect the specific requirements of the Senior Data-Driven Research Engineer role. We love seeing candidates who take the time to connect their experience with what we’re looking for.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate straightforward communication, so make sure your key achievements and experiences stand out without unnecessary fluff.
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 don’t miss any important updates from our team!
How to prepare for a job interview at Synthesia
✨Know Your Data Inside Out
Make sure you’re well-versed in the data lifecycle and how it impacts model performance. Brush up on your experience with data quality and workflow orchestration systems, as these will likely come up during the interview.
✨Showcase Your Python Skills
Prepare to discuss specific projects where you’ve used Python to manipulate datasets or build pipelines. Be ready to share code snippets or examples that highlight your problem-solving skills and technical expertise.
✨Understand Human-Centric Design
Since the role involves building a human-centric data lake, think about how you can articulate your approach to making data accessible and useful for researchers. Have examples ready that demonstrate your ability to collaborate with model training teams.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s current data challenges and future goals. This shows your genuine interest in the role and helps you assess if the company aligns with your career aspirations.
