Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI.

What is The Role

In October 2025, Elastic acquired Jina AI, a team that spent six years building Search Foundation Models. We develop world-class embedding models, rerankers, and retrieval systems—from multilingual to multimodal, from 8K context windows to binary quantization. Our models see 5M+ downloads monthly on HuggingFace and process 200B+ tokens daily through our APIs. We publish at NeurIPS, ICLR, ICML, EMNLP because we believe shipping a model without a paper is shipping without understanding.

We operate as a focused, high-output team of ~20 people. Our structure is flat, our feedback loops are short, and everyone—including leadership—writes code and ships models. We believe that in a fast paced field, extreme focus and efficient execution are what separate good teams from great ones.

We're now building out the Search Foundation Models at Elastic and looking for exceptional researchers to join us.

What You Will Be Doing

Architectures: Encoder/decoder designs, single vs. multi-vector representations, early vs. late interaction mechanisms
Scale & Efficiency: Long-context retrieval (8K+), sparse embeddings, low-bit/binary quantization, Matryoshka representation learning
Modalities: Multilingual models, multimodal/omni retrieval, vision-based document understanding
Training: Synthetic data generation for hard negative mining, retrieval model distillation, learning directly from embedding space
Emerging Directions: R1-style reasoning retrieval models, task-specific vs. multi-task training strategies

What You Bring

PhD or MSc in Computer Science, Machine Learning, NLP, or related field
3+ years of experience training production models (full training pipelines, not only fine-tuning)
3+ years of professional Python development (PyTorch, Transformers, distributed training)
Strong foundation in information retrieval and neural search
Track record of publications at major venues (ACL, EMNLP, NeurIPS, ICML, ICLR, or equivalent)

Bonus Points

Experience training embedding models or rerankers
Understanding of token economics: batch sizes, throughput, latency, and context length tradeoffs
Ability to rapidly prototype—read a paper and have a working experiment within days
Contributions to open-source ML projects
Familiarity with retrieval benchmarks and their limitations

Additional Information - We Take Care of Our People

As a distributed company, diversity drives our identity. Whether you’re looking to launch a new career or grow an existing one, Elastic is the type of company where you can balance great work with great life. Your age is only a number. It doesn’t matter if you’re just out of college or your children are; we need you for what you can do.

We strive to have parity of benefits across regions and while regulations differ from place to place, we believe taking care of our people is the right thing to do.

Competitive pay based on the work you do here and not your previous salary
Health coverage for you and your family in many locations
Ability to craft your calendar with flexible locations and schedules for many roles
Generous number of vacation days each year
Increase your impact - We match up to $2000 (or local currency equivalent) for financial donations and service
Up to 40 hours each year to use toward volunteer projects you love
Embracing parenthood with minimum of 16 weeks of parental leave

Different people approach problems differently. We need that. Elastic is an equal opportunity employer and is committed to creating an inclusive culture that celebrates different perspectives, experiences, and backgrounds. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, pregnancy, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, disability status, or any other basis protected by federal, state or local law, ordinance or regulation.

We welcome individuals with disabilities and strive to create an accessible and inclusive experience for all individuals. To request an accommodation during the application or the recruiting process, please email [email protected]. We will reply to your request within 24 business hours of submission.

Applicants have rights under Federal Employment Laws, view posters linked below: Family and Medical Leave Act (FMLA) Poster; Pay Transparency Nondiscrimination Provision Poster; Employee Polygraph Protection Act (EPPA) Poster and Know Your Rights (Poster)

Elasticsearch develops and distributes encryption software and technology that is subject to U.S. export controls and licensing requirements for individuals who are located in or are nationals of the following sanctioned countries and regions: Belarus, Cuba, Iran, North Korea, Russia, Syria, the Crimea Region of Ukraine, the Donetsk People’s Republic (“DNR”), and the Luhansk People’s Republic (“LNR”). If you are located in or are a national of one of the listed countries or regions, an export license may be required as a condition of your employment in this role. Please note that national origin and/or nationality do not affect eligibility for employment with Elastic.

Please see here for our Privacy Statement.

Senior AI Research Engineer

AI overview

What is The Role

What You Will Be Doing

What You Bring

Bonus Points

Additional Information - We Take Care of Our People

Perks & Benefits Extracted with AI