Software Engineer (Open-Source) (f/m/d)

Remote /
Engineering /
Full Time
/ Hybrid
🙌 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 four offices: Berlin (HQ), San Jose, 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

What you should bring to the team:
- A passion and deep understanding of software engineering, multi-modal Machine Learning, and their applications (e.g.: search and creative AI)
- A passion for contributing to Open Source projects
- A motivation for solving real-world problems and delivering outstanding user experiences
- A team player mindset, where you enjoy working in a collaborative environment
- A proactive take on ownership of your projects

Responsibilities:

    • Contribute and push the boundaries of DocArray and other open-source products to create the best ecosystem for multi-modal machine learning.
    • Make sure that DocArray and the Jina ecosystem are up to date with the latest AI technology
    • Collaborate with internal and external stakeholders to integrate new features into the ecosystem
    • Build connections between DocArray and other tools in the open-source ML landscape
    • Interact with the open source communities and promote the product by giving technical talks at conferences and meetups or writing an instructional and technical blog post

Qualifications:

    • A Bachelor’s degree or equivalent professional experience
    • Strong programming skills in python and familiarity with other programming languages (Rust, C++, Golang …) is a bonus
    • Strong will to build open-source software and to create frameworks that people will love to use
    • Good Knowledge of the python ML ecosystem (Numpy, scikit learn, pytorch, … )
    • Interested in ML and AI, experience in multi-modal machine learning is a bonus
    • (Bonus): Experience building real-world search applications (ElasticSearch, Redis, vector database ..)
    • (Bonus): Open-source contribution and/or being the maintainer of (relatively) successful open-source projects



😊 Benefits & Perks

💰 Competitive salary & stock options
🌎 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. For engineering candidates, after this interview candidates will receive an email and be asked to complete an offline code challenge. On average the candidates can finish it in 30 minutes.

- Next, candidates will be invited to schedule Peer Interviews with team members from the relevant team. There are two rounds of Peer Interview, 1st is Technical Peer Interview and the 2nd is Team Peer Interview. For engineering candidates, the team will examine the quality of the offline challenge as well as you fundamental knowledge and coding skill during the Technical Peer Interview; one should also expect a live-coding challenge in 10 to 15 minutes. As long as candidates passed the Technical Peer Interview, they will be invited to talk with specific Team Lead in the Team Peer Interview stage. The interview will be more relevant to practical problem solving.

- Finally, candidates will be invited to schedule a 30-minute interview with CXO.

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.