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Senior Data Engineer

   "The AI company that's revolutionizing Hollywood"


Flawless is shattering the boundaries of traditional filmmaking with its groundbreaking suite of Gen AI film editing tools. Our mission is to empower filmmakers with cutting-edge technology that allows creativity without compromise, expands storytelling possibilities, and delivers unparalleled visual and emotional experiences. We are also setting new standards in ethical AI by creating the Artistic Rights Treasury (A.R.T.), a rights management solution designed to protect artists and rights holders within the Entertainment landscape.


Reports to: ML Engineering Manager


What we are looking for:

A Senior Data Engineer, who is passionate about building platforms that massively reduce lead time from bringing Machine Learning research to production. The vision of the Data team is to enable our cross functional ML teams to spend most of their time solving tricky ML problems rather than dealing with data engineering/infra/ops challenges.

You will lead on setting the bar for the quality and accessibility of our data, working to source and catalogue high quality datasets and build automated annotation pipelines. You have a solid background in core software engineering principles, are happy deploying & managing infrastructure, and have a good understanding of the difficulties faced by research scientists and ML engineers.


Responsibilities
  • Building & maintaining data annotation pipelines, establishing the workflow for continuous data delivery and annotation.
  • Work with our ML teams to build data transformation pipelines for large scale computer vision datasets
  • Establish robust data quality metrics and drive a continual improvement of data quality and diversity\
  • Drive standardisation of data management and exchange.
  • Support Flawless data sourcing efforts, license management and data governance strategy.
  • Working with our Platform team, supporting efficient data storage and transportation and access.


Qualifications
  • Strong analytical background: BSc or MSc in data engineering/machine learning or related topics 
  • Programming experience with Python.
  • Experience creating and managing large scale datasets for machine learning, including establishing quality metrics. 
  • Experience setting up infrastructure at scale for ML / Data Teams, including CI/CD & Data pipelines
  • Experience working with cloud platforms (AWS, GCP, Azure) and familiarity with infrastructure as code.


Preferred Qualifications
  • Experience within an early-stage data function, having played a key role in helping the data team develop into a more mature function during your tenure
  • Experience working with the AWS Data Stack
  • Experience working with large scale data, preferably in the Computer Vision domain
  • Experience with multi-stage data transform pipelines, and large model training with 1000s of hours of content


$180,000 - $225,000 a year

Interview Process:

At Flawless, our team and interview process want to help you show your best self. We’ll dive into past projects and simulate working together. Our interview process is four rounds with some casual Zoom (or in-person) coffee in between to get to know each other: 


- Recruiting Screen: 30-45 minute call with our recruiting team (We want to discuss your background, interests and motivations as well as the practical details and make sure that Flawless would be a good fit for you)

- Hiring Manager Screen: 45-60 minute zoom interview - you will meet with our Platform ENgineering Leadership to discuss your technical expertise.

- Reverse System Design: 60 Minute zoom interview where you will meet 1-2 members of the Platform Engineering team, through a screen share format talking through experience in data transformation.

- Final Interview: 60 Minute onsite interview - Use this time to meet other ML members on the team, discussing data operations, and ML Operations.


Your Recruiter and hiring manager will be your main point of contact and prepare you for interviews. You’ll meet 4 to 6 people from across the business. (We make sure that you have time in each interview to ask them questions). If we don’t give an offer, we’ll provide feedback!


Why work at Flawless?

You will be working in an environment based on trust, autonomy and collaboration, and this is a great opportunity for someone who wants to be part of a growing company in its most exciting stage of development. You can play a part in shaping the future of a company that’s caring, creative and collaborative.


In addition to this, you'll also receive: 

- Autonomy

- A hybrid working environment

- Competitive Salary

- Stock Options


Flawless is proud to emphasize an equal opportunity, safe environment for people to do their best work. We are committed to providing equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.

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CEO of Flawless AI
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Scott Mann, Nick Lynes
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Average salary estimate

$202500 / YEARLY (est.)
min
max
$180000K
$225000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Senior Data Engineer, Flawless AI

Join Flawless, a trailblazer in the world of artificial intelligence that's transforming Hollywood, as a Senior Data Engineer! Based in the vibrant Santa Monica, CA, our goal is to revolutionize the filmmaking process with innovative Gen AI film editing tools, and we're on the lookout for passionate individuals to join our team. In this pivotal role, you'll be at the forefront of building platforms that minimize the time it takes to transition machine learning research to production. Your expertise will drive the quality and accessibility of our data, helping to source and catalogue high-quality datasets while creating automated annotation pipelines that streamline our ML processes. You'll collaborate closely with our cross-functional ML teams, tackling large-scale computer vision datasets and enhancing data delivery workflows. If you have a strong analytical background, proficiency in Python, and are experienced in setting up cloud infrastructures, you'll fit right into our dynamic and collaborative environment. At Flawless, we pride ourselves on ethical AI practices, as showcased by our Artistic Rights Treasury (A.R.T.). This unique role not only empowers your career but also allows you to make a significant impact on how technology intersects with creativity in the film industry. We're excited to help you grow in your career while contributing to a safe, equal opportunity environment where creativity flourishes!

Frequently Asked Questions (FAQs) for Senior Data Engineer Role at Flawless AI
What are the primary responsibilities of a Senior Data Engineer at Flawless?

As a Senior Data Engineer at Flawless, your primary responsibilities include building and maintaining data annotation pipelines, establishing robust workflows for continuous data delivery, and collaborating with ML teams to create data transformation pipelines for large-scale computer vision datasets. You'll also focus on driving data quality metrics, ensuring diverse datasets, and supporting efficient data storage and access strategies.

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What qualifications does Flawless seek for the Senior Data Engineer position?

Flawless looks for candidates with a BSc or MSc in data engineering, machine learning, or related fields. You should have programming experience in Python and demonstrate expertise in managing large-scale datasets for machine learning, creating quality metrics, and setting up infrastructure in cloud environments like AWS, GCP, or Azure.

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How does Flawless support its Senior Data Engineers in professional development?

Flawless fosters an environment of trust and collaboration, providing Senior Data Engineers with autonomy and opportunities to shape their roles. The company emphasizes mentorship and continuous improvement, enabling you to grow alongside your team while tackling cutting-edge projects that enhance your skills and expertise.

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What technologies and tools will I work with as a Senior Data Engineer at Flawless?

In your role at Flawless, you will work with a variety of tools and technologies, including Python for programming, cloud platforms like AWS, GCP, and Azure for infrastructure, as well as data management tools for creating and tracking quality datasets. Your experience with CI/CD processes and data pipelines will be essential in ensuring project success.

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What is the company culture like at Flawless for the Senior Data Engineer position?

Flawless promotes a culture of creativity, collaboration, and ethical AI practices. As a Senior Data Engineer, you'll find a supportive environment that values your contributions, encourages your ideas, and fosters an atmosphere of innovation. With a hybrid work model, you'll be able to balance collaboration with personal productivity seamlessly.

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Common Interview Questions for Senior Data Engineer
Can you describe your experience with building data annotation pipelines?

When answering this question, highlight specific projects where you developed data annotation pipelines, detailing the technologies you used and the impact of your work on the overall data workflow. Discuss any challenges you faced and how you overcame them to ensure efficient data processing.

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How do you ensure the quality and integrity of large-scale datasets?

Talk about your approach to establishing quality metrics and processes. Include examples of how you've implemented validation and verification steps to maintain data integrity, as well as any tools or methodologies you've used to monitor data quality over time.

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What challenges have you faced when managing cloud infrastructure, and how did you overcome them?

Discuss specific examples of challenges such as performance, scaling issues, or cost management in cloud environments. Explain the solutions you implemented, including details on monitoring tools or practices that allowed you to optimize performance and manage resources more effectively.

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How do you prioritize and manage multiple data projects concurrently?

Explain your strategy for assessing project urgency and importance. Describe your methods for setting timelines, communicating with stakeholders, and perhaps employing project management tools or frameworks to keep all team members aligned and informed.

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Can you give an example of a successful collaboration with ML teams?

Provide a detailed example where you worked closely with ML teams, outlining your role and how your contributions directly supported their research and development efforts. Highlight the outcomes of this collaboration and any recognition you received.

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Describe your experience with infrastructure as code.

Share specific tools you have experience with, such as Terraform or CloudFormation, and how you’ve utilized them to manage infrastructure efficiently. Discuss any projects where implementing infrastructure as code significantly streamlined workflows or improved scalability.

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What techniques do you use for data transformation in machine learning?

Describe the various techniques you've used for data transformation, such as normalization, feature engineering, or dimensionality reduction. Provide examples of how these techniques improved model performance or contributed to the success of specific projects.

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How do you stay updated with the latest trends in data engineering and machine learning?

Mention your strategies for continuous learning, whether through following industry experts on social media, participating in webinars, attending conferences, or taking online courses. Highlight any specific sources or networks you find particularly valuable.

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What do you view as the biggest challenge in the data engineering field today?

Offer your insights on current challenges facing data engineering, such as data privacy concerns, the need for real-time processing, or the integration of new technologies. Discuss how you believe these challenges can be addressed within an organization.

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Why are you interested in working for Flawless as a Senior Data Engineer?

Convey your enthusiasm for Flawless and its mission. Discuss how your values align with the company’s focus on ethical AI and creativity in filmmaking. Emphasize how your skills and experiences make you a perfect fit for making a significant impact at Flawless.

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The process of dubbing a film into a foreign language hasn’t changed much over the past century. When a movie is dubbed, the dialogue often gets changed to fit an actor’s mouth movements, which leads to two big problems: first, the new dialogue n...

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Full-time, hybrid
DATE POSTED
January 10, 2025

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