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Software Engineer for Training AI Data - Python, French Language

Accepted Locations and Languages

We accept native or highly fluent French speakers based in Metropolitan France. For the complete list of accepted locations, click here. This work is 100% remote.

Loom Video

Our Founder/CEO, Gabe Greenberg, created a more in-depth Loom video that we highly recommend you watch! Check it out here: https://www.loom.com/share/5a8972c7fbbf46aaa3f389b2b6391c40

Overview

You’ll join an expert annotation team to create training data for the world's most advanced AI models. No previous AI experience is necessary. You'll get your foot in the door with one of the most prominent players in the AI/LLM space today. We seek software engineers with 3+ years of experience to train large AI language models, helping cutting-edge generative AI models write better code. Projects typically include discrete, highly variable problems that involve engaging with these models as they learn to code. We currently have 200+ roles open!

What Will I Be Doing?

  • Evaluating the quality of AI-generated code, including human-readable summaries of your rationale

  • Solve coding problems, writing functional and efficient code

  • Writing robust test cases to confirm code works efficiently and effectively

  • We asked the technical project manager to go into even more detail and this is how he answered: It is solving coding challenges, creating instructions to help others, reviewing the code before it goes into the model, and there's a ton of variety in the projects. We have everything from "Which piece of Python code is better?" to "Make a full mobile application using this chatbot, and improve the chatbot's responses afterward to make it faster."

Pay Rates

  • France: $27.93/hr

  • For other countries, see this list.

  • Expectations are 15+ hours per week; however, there is no upper limit. We have engineers working 20-40 hours per week and some working 40+ hours per week. You can work as much as you want to. You'll get paid weekly per hour of work done on the platform.

Contract Length

  • Long term, there is no end date. They expect to have work for the next 2 years.

  • You can end the contract at any time. We hope you will commit to 12 months of work, but if you start and it's not a fit for you, we totally understand.  

Flexible Schedules

  • Developers can set their own hours—ideal candidates will be interested in spending 40 hours a week. They will be with teams, so strong performers will adapt to the urgency of projects and stay engaged, but they will also be incredibly flexible on working hours. 

  • You can take a 3-hour lunch, no problem. Instead of tracking your hours, you are paid according to time spent on the platform, calculated in the coding exercises.  

Interview Process

  1. Apply using this Ashby form.

  2. If you seem like a good fit, we'll send an async RLHF code review that will take 35 minutes and must be finished within 72 hours of us sending it.

  3. You'll receive credentials to the RLHF platform. We'll then set up a group call to answer any further questions about onboarding with the company.

  4. You'll perform a simulated production-level task (RLHF task) on the platform. This will be your final interview, which will ultimately determine your employment and leveling. Successful completion of this process provides you with an opportunity to work on projects as they become available.

Tech Stack Priorities

  • The current priority for this team is engineers with either a Data Science background who know Python well or software engineers who are well versed in Python.

Required Qualifications:

  • 3+ years of experience in a software engineering/software development role.

  • Complete fluency in the English language.

  • Ability to articulate complex scientific concepts clearly and engagingly.

  • Excellent attention to detail and ability to maintain consistency in writing.

  • Solid understanding of grammar, punctuation, and style guidelines.

  • Proficiency with Python

Nice To Haves:

  • Bachelor's or Master’s degree in Computer Science

  • Proficiency in working with one or more of the following: Java, JavaScript, TypeScript, C++. SQL, Swift, Ruby, Rust, Go, NET, Matlab, PHP, HTML, DART, R, Apex, and Shell, C, C#

  • Recognized accomplishments or contributions to the coding community or in projects.

  • Proven analytical skills with an ability to approach problems creatively.

  • Adept communication skills, especially when understanding and discussing project requirements.

  • A commitment to continuous learning and staying updated with the latest coding advancements and best practices.

  • Enthusiasm for teaching AI models and experience with technical writing!

Average salary estimate

$87030 / YEARLY (est.)
min
max
$57900K
$116160K

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 Software Engineer for Training AI Data - Python, French Language, G2i Inc.

If you're a passionate Software Engineer with a knack for Python and fluent in French, we have an awesome opportunity for you! Join our team to create innovative training data for leading AI models at a renowned tech company. In this fully remote role, you’ll become part of an expert annotation team, designing solutions to train powerful language models to improve their coding skills. With at least 3 years of experience under your belt, you’ll dive into diverse projects, from evaluating AI-generated code to crafting new coding challenges. There’s no need for prior AI experience; we aim to support you in mastering these technologies. Imagine writing code that trains AI to write better code in return! You’ll work flexible hours tailored to your schedule, making it easy to maintain a work-life balance. And, with the expectation of 15+ hours a week—without an upper limit—you can take on as much as you want. Our CEO, Gabe Greenberg, shares valuable insights about the role in a Loom video; it’s definitely worth a watch! Plus, we offer competitive pay rates of $27.93/hr specifically for candidates based in France. So if you’re ready to embrace the future of coding alongside cutting-edge technology, and you have a strong foundation in Python, this Software Engineer position could be your next big step!

Frequently Asked Questions (FAQs) for Software Engineer for Training AI Data - Python, French Language Role at G2i Inc.
What are the responsibilities of a Software Engineer for Training AI Data at this company?

As a Software Engineer for Training AI Data at our company, your main responsibilities include evaluating AI-generated code, solving unique coding challenges, and writing robust test cases to ensure effective performance. You’ll engage hands-on with different AI models as they learn coding and contribute to creating instructions for those models. This collaborative role ensures a variety of projects, keeping your work dynamic and engaging.

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What qualifications do I need to apply for the Software Engineer role focused on AI Data?

To be considered for the Software Engineer for Training AI Data role, you should have at least 3 years of experience in software engineering, alongside complete fluency in the English language. A strong proficiency in Python is essential, as well as excellent communication skills and attention to detail, helping you articulate complex concepts clearly.

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What languages and locations are accepted for the Software Engineer for Training AI Data position?

For the Software Engineer for Training AI Data position, we specifically accept native or highly fluent French speakers based in Metropolitan France. This role is completely remote, allowing flexibility for candidates across different regions, as long as they fit these language requirements.

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What is the pay rate for the Software Engineer role focusing on training AI data?

The pay rate for the Software Engineer for Training AI Data position in France is $27.93 per hour. There’s flexibility in your working hours, and you can choose to work more than the expected 15+ hours per week, allowing you to maximize your earnings while enjoying the flexibility to manage your own schedule.

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How does the interview process work for the Software Engineer for Training AI Data role?

The interview process for the Software Engineer for Training AI Data role involves several steps. First, you apply through our form. If selected, you'll complete an RLHF code review within 72 hours. Afterward, you will access the RLHF platform for further onboarding discussions, followed by a simulated production-level task to assess your suitability for the role.

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Common Interview Questions for Software Engineer for Training AI Data - Python, French Language
Can you describe your experience with Python and how it relates to AI?

In discussing your experience with Python, highlight specific projects where you utilized Python for data manipulation, automation, or AI-related tasks. Emphasize your ability to write efficient code and how you’ve engaged with libraries like NumPy, pandas, or TensorFlow in prior roles.

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How do you approach problem-solving when coding?

When discussing your problem-solving approach, outline your process for breaking down complex coding challenges into smaller components. Mention how you analyze requirements first, explore possible solutions, and test your code thoroughly for effectiveness and efficiency.

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What strategies do you use to keep up with coding best practices?

Discuss your strategies for continuous learning, such as following tech blogs, participating in coding workshops, and engaging with community forums. Highlight your commitment to implementing the latest best practices in your development work, showcasing your proactive approach to skill enhancement.

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Can you explain a time you had to improve an AI model's performance?

When addressing this question, describe a specific project where you successfully enhanced an AI model's performance. Detail the steps you took to analyze its performance metrics, your rationale for necessary improvements, and the results post-implementation, emphasizing your critical thinking and analytical skills.

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How do you ensure the quality of your code?

To ensure code quality, you might discuss your practices around writing unit tests, engaging in code reviews, and adhering to coding standards such as PEP8 for Python. Share examples of how these practices have positively impacted your previous projects.

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What interests you about working with AI technologies?

Express your passion for cutting-edge technology and your enthusiasm for how AI is shaping the future. You could also mention specific trends or breakthroughs in AI that inspire you, and how you see your role in contributing to this evolving landscape.

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How do you handle tight project deadlines?

When discussing tight deadlines, emphasize your organizational skills, ability to prioritize tasks, and your experience working collaboratively with teams to meet deliverables. Highlight techniques you employ to remain focused and efficient under pressure, showcasing your time management capabilities.

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What tools or technologies are you familiar with that complement your Python skills?

Mention any additional tools or technologies that pair well with your Python skills, such as version control systems like Git or cloud platforms like AWS. Share experiences of how you've integrated these tools into your workflows to increase efficiency or enhance project outcomes.

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How do you communicate complex concepts to non-technical stakeholders?

Explain your approach to simplifying complex technical concepts by using analogies or visual aids. Share experiences where you successfully presented technical information to non-technical audiences and the importance of clear communication in ensuring project success.

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What is your approach to gathering and analyzing user feedback on AI-generated code?

Discuss your systematic approach to collecting and analyzing user feedback, including methods like surveys, direct interviews, or analytics tools. Emphasize the importance of continuous improvement based on feedback and how it informs your coding practices and AI training efforts.

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