Senior Research Scientist

Key Skills

Algorithms, Collibra, NeurIPS, Python Programming, PyTorch, TensorFlow

Job Description

 Who are we?

Founded in February 2020, Jina AI has swiftly emerged as a global pioneer in multimodal AI technology. Within an impressive timeframe of 20 months, we have successfully raised $37.5M, marking our strong position in the AI industry. Our ground-breaking technology, open-sourced on GitHub, has empowered over 40,000 developers around the globe to seamlessly build and deploy sophisticated multimodal applications.

In 2023, we've made significant strides in advancing AI generation tools grounded on multimodal technology. This innovation has benefited over 250,000 users worldwide, catering to a plethora of unique business requirements. From facilitating business growth and enhancing operational efficiency to optimizing costs, Jina AI is dedicated to empowering businesses to excel in the multimodal era.

 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

Jina AI is seeking a talented Senior Research Scientist to join our team and help drive the development of groundbreaking AI technologies.

As a key member of our research team, you will focus on the design and implementation of LLMs such as GPT, BERT, and Transformer architectures, and multimodal models in resource-constrained settings, including on-prem, privacy-preserved, and low VRAM environments. This role is crucial to our mission to innovate and make breakthroughs in the AI industry.

Responsibilities

Conduct cutting-edge research in LLMs, multimodal models, and resource-constrained settings, contributing to the company's overall research agenda.

Develop and implement novel algorithms, techniques, and models using state-of-the-art approaches such as fine-tuning methods, federated learning, and knowledge distillation.

Collaborate with the research team, as well as external partners, to enhance our research capabilities and drive innovation.

Publish research findings in top-tier conferences and journals such as NeurIPS, ICML, and ACL, and present at industry events to showcase our advancements and maintain our position as an industry leader.

Provide technical guidance and mentorship to junior researchers and engineers, fostering a culture of collaboration and continuous learning.

Stay up-to-date on industry trends, competitor activities, and emerging technologies to ensure our research remains relevant and cutting-edge.

Required Qualifications

PhD in Computer Science, Artificial Intelligence, or a related field.

4+ years of experience in AI research, with a focus on LLMs and multimodal models.

Strong track record of published research and conference presentations in relevant fields, particularly at top-tier conferences such as NeurIPS, ICML, and ACL.

Proficient in Python, TensorFlow, PyTorch, and other relevant AI and machine learning frameworks.

Experience with advanced techniques in fine-tuning, federated learning, and knowledge distillation for LLMs and multimodal models.

Strong problem-solving skills and the ability to work in a fast-paced, dynamic environment.

Excellent communication and collaboration skills, with experience mentoring and guiding junior team members.

 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, Shenzhen and 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.