Machine Learning Intern (f/m/d)

🙌 Who are we?

-A commercial open-source company that empowers businesses and developers to create cutting-edge neural search, generative AI, and multimodal services using state-of-the-art LMOps, MLOps, and cloud-native technologies

- Founded in Feb. 2020, raised $37.5M in 20 months. Now a global team of 65 with three offices: Berlin (HQ), Shenzhen, and Beijing.

- One of the high-valued & high-potential AI startups in the world, featured on Forbes DACH AI30 2020, CBInsights AI 100 2021 & 2022.

✨ Who do we want?

- You are passionate about multimodal intelligence and making it accessible to everyone.

- You want to work with the latest technologies and are fascinated by AI/ML.

- You are a fast learner and a team player and enjoy working in an async, distributed environment.

- You are proactive and take ownership of your projects.

- You have excellent communication skills in English.

💁 About this position

Please, note that we are looking for someone that can join us in our Berlin office and that we are not offering visa sponsorship for this role at the moment.

Your main responsibilities would be:

Develop and Train State-of-the-Art Embedding Models: As an active team member, you will play a key role in the development and training of advanced multilingual text embedding models. Your expertise will contribute to producing high-quality vector embeddings, pushing the boundaries of what’s possible in NLP.

Advance Multimodal Embedding Research: You will also be involved in the development and training of state-of-the-art text-image vector embeddings. Your contributions will be instrumental in leveraging the power of multimodal learning to unlock new possibilities in understanding and analyzing data.

Integration and Maintenance: Your responsibilities will extend beyond model development. You will be responsible for integrating our models into our production codebase, ensuring seamless deployment, and collaborating with the team to maintain our Huggingface repository.

Communicate Findings: Your role will include summarizing research findings and insights into technical reports and blog posts. This will help the broader community understand and benefit from the advancements made by our team.

Requirements for this position would include:

Solid background in natural language processing (NLP) and/or computer vision, with a focus on building and training vector embeddings.

Experience in working with multilingual data and understanding the challenges involved in cross-lingual embeddings.

Proficiency in relevant deep learning frameworks and libraries for training embedding models.

Demonstrated ability to work collaboratively in a team environment and contribute to research projects.

Strong communication skills to effectively convey technical concepts in writing and presentations.

Preferred Qualifications:

Published research papers or contributions to open-source projects in the fields of NLP or computer vision.

Familiarity with Pytorch & Huggingface ecosystem and experience maintaining repositories.

Knowledge of industry best practices in model training.

😊 Benefits & Perks

💰 Competitive salary

🌎 Multi-cultural & diverse team

🎓 Numerous opportunities to present/attend top AI/OSS/industry conference

🦄 Rapid career development opportunities alongside the company

🏢 Central office in downtown Berlin, San Jose, Shenzhen, Beijing

⛱️ Free snacks & drinks, monthly team events, flexible working hours, home office options

💻 Macbooks & top-notch equipment

💼 Hiring Process

Candidates can expect the hiring process to follow the order below. Please keep in mind that candidates can be declined from the position at any stage of the process.

- The first round is the CV screening, candidates will receive an email that contains a link for booking the next round. This process takes a maximum of one week.

- Qualified candidates will be invited to schedule a 30-minute screening call specifically on Zoom with one of our global recruiters.

- Next, candidates will be invited to a Technical Peer Interview. During the interview, which will last 1 hour, the team will examine your fundamental knowledge and coding skills as well as your motivation to join Jina AI; one should also expect a live-coding challenge in 10 to 15 minutes.

We will collect the feedback from all interviewers and make a decision in a maximum of two weeks (on average it takes 5 working days). Then the candidate will be invited to another 15-minute call with our recruiters to discuss the terms of the offer.

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Machine Learning Intern (f/m/d)

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