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- Tasks: Join a team to develop and evaluate cutting-edge generative AI models.
- Company: Dynamic tech company focused on innovative AI solutions.
- Benefits: Competitive salary, flexible hours, and opportunities for growth.
- Why this job: Make a real impact in the exciting world of AI and technology.
- Qualifications: STEM degree or equivalent experience; knowledge of Python, Unix, and SQL.
- Other info: Collaborative environment with hands-on experience in AI development.
The predicted salary is between 36000 - 60000 £ per year.
Despite rapid development in generative AI, quality measurement remains challenging due to the lack of reliable and robust technical metrics. This is especially the case when the slight differences in the details generated by the model could have a significant impact on user experience. In this team, we are developing a series of manual (human rating), semi-automatic, and fully automatic evaluations to measure the quality of our image and video generative models (text to image, image to video, text to video, etc.) in a variety of quality axes, including visual quality, prompt following, identity preservation, naturalness, and visual text generation.
To this end, we require the support of 10 additional data analysts, 5 for image in MPK and 5 for video in LON, to work closely with the team to prototype and iterate on the measurements before they are scaled up.
Job Responsibilities:- Working with the team to prototype human rating and semi-automatic model evaluation protocols.
- For high stake and/or high complexity protocols, conduct small-to-medium scale in-house human rating on generated content.
- Working with engineers to identify and summarize model gaps based on the above evaluation.
- Working with engineers to identify data needed to close those gaps and mine such data to prepare training data for the next iteration of model training.
- Working with PDO teams to scale up validated evaluation protocols, including coordination and auditing.
- Verbal and written communication skills, problem solving skills, and interpersonal skills.
- Attention to details and an aptitude for experimental investigations.
- Basic ability to work independently and manage one’s time.
- Basic knowledge of Python, Unix, and SQL.
- Basic knowledge of computer vision and generative models.
- Associate's degree or equivalent training required in Computer Science, Electronic Engineering, Physics, Bioinformatics, or other STEM subjects.
- Prior industrial experience in software development and testing and/or research experience in human-computer interaction are preferred.
- Be onsite, in MPK/LON, working with engineers.
System Analyst employer: Morgan McKinley
Contact Detail:
Morgan McKinley Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land System Analyst
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those already working at companies you're eyeing. A friendly chat can open doors and give you insider info on what they're really looking for.
✨Tip Number 2
Prepare for interviews by diving deep into the role. Understand the technical metrics and evaluation protocols mentioned in the job description. We want to see you shine with your knowledge about generative models and how they impact user experience.
✨Tip Number 3
Showcase your problem-solving skills during interviews. Bring examples of how you've tackled challenges in past projects, especially if they relate to data analysis or model evaluation. We love hearing about your hands-on experience!
✨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.
We think you need these skills to ace System Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the System Analyst role. Highlight any relevant projects or experiences in generative models, Python, or data analysis to catch our eye!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about quality measurement in AI and how your background makes you a great fit for our team. Keep it engaging and personal!
Show Off Your Attention to Detail: In this role, attention to detail is key. Make sure your application is free from typos and errors. A polished application shows us you care about quality, just like we do!
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 Morgan McKinley
✨Know Your Tech
Brush up on your knowledge of Python, Unix, and SQL before the interview. Be ready to discuss how you've used these skills in past projects or experiences, especially in relation to data analysis and model evaluation.
✨Showcase Your Problem-Solving Skills
Prepare examples that highlight your problem-solving abilities. Think about times when you identified gaps in a project or improved a process, particularly in software development or human-computer interaction.
✨Communicate Clearly
Since verbal and written communication skills are key for this role, practice explaining complex concepts in simple terms. You might be asked to describe your approach to evaluating generative models, so clarity is crucial.
✨Demonstrate Attention to Detail
Be prepared to discuss how you ensure accuracy in your work. Whether it's through meticulous data analysis or careful protocol development, showing that you value detail will resonate well with the interviewers.
