Principal Research/Data Scientist, Elastic

Platform, ML R&D

$159.8-303.5k

Actual salary range is dependent on location. This role is currently eligible to participate in Elastic's stock program

Python

PyTorch

Senior and Expert level

Remote from Canada, Ireland, Spain, UK, US

Software that searches and analyses data in real time

Be an early applicant

Software that searches and analyses data in real time

1001+ employees

B2BAnalyticsSaaS

Be an early applicant

$159.8-303.5k

Actual salary range is dependent on location. This role is currently eligible to participate in Elastic's stock program

Python

PyTorch

Senior and Expert level

Remote from Canada, Ireland, Spain, UK, US

1001+ employees

B2BAnalyticsSaaS

Company mission

To build software to make data usable in real-time and at scale for search, logging, security, and analytics use cases.

Job

Company

Role

Who you are

Excellent comprehension of the industrial and academic state of the art on xLMs, more specifically in retrieval and reranking techniques
Extensive professional experience in designing, training, and debugging various model architectures as well testing and implementing post-training strategies; proven track record of assessing, proposing and integrating frontier techniques to large scale products
6+ years of professional software development experience in Python (pytorch)
Experience with large-scale model training (between 0.1 and 7B parameters), distributed training, and model optimization techniques (e.g., quantization, pruning, efficient attention mechanisms)
Excellent communication skills and gentle approach to leadership
Strong attention to detail and highly organized

What the job involves

The R&D ML team is responsible for training, testing and optimizing a set of models and pipelines used across the whole stack
As a model architecture lead for retrieval and reranking, you will lead the design and post-training strategies of our next generations of in-house models that will be integrated in our product
While our current generation of models are text only, we plan to add multi modality in the near future
This is an outstanding opportunity to lead our effort and contribute to shipping the upcoming generation of Elastic’s models, which will then be served to our broad userbase
Strategic research & technical roadmap definition: identify promising new technologies for text-only and multi-modal models, look into post-training methodologies relevant for retrieval and re-ranking, and champion solutions that will fit best in Elastic
Tooling: improve our infrastructure and help scale to accommodate larger models: provide expert guidance on distributing data preparation, training and testing on multiple GPUs, help design, improve and write specs for our compute infrastructure
Model variants exploration: investigate applying fine-tuning, quantization, distillation and other techniques to existing or upcoming models
Technical leadership: foster a culture of innovation and rigorous experimentation, coordinate knowledge sharing within the team; act as a senior technical authority and go-to expert for the modeling, training and testing challenges; mentor more junior members of the team helping them develop their skills and knowledge
Communication: interact with various leads across the organization, communicate sophisticated concepts to high profile stakeholders, adjust and iterate on the roadmap according to internal and external inputs

Our take

Elastic develops the Elastic Stack, an open-source set of tools that includes Elasticsearch, Kibana, Beats, and Logstash, designed for data search and analysis. It also offers X-Pack, which adds commercial features to the Elastic Stack, and Elastic Cloud, a suite of SaaS (Software-as-a-Service) products.

This technology is widely used by major companies like eBay, Wikipedia, Yelp, Uber, Lyft, Tinder, and Netflix, along with over 17,000 other organizations. It is applied in various use cases, including application and website search, enterprise search, logging, infrastructure monitoring, application performance management (APM), security analytics (enhancing SIEM applications), and business analytics.

Freddie

Company Specialist at Welcome to the Jungle

Insights

Top investors

8% employee growth in 12 months

Glassdoor (3.8)

Company

Funding (last 2 of 4 rounds)

Jul 2016

$58m

SERIES D

Jun 2014

$70m

SERIES C

Total funding: $162m

Company benefits

Toast to your health: Fully paid health coverage for you and your family, in many locations
Craft your calendar: Flexible location and schedule for most roles
Create space for you: Distributed by design workforce, plus generous number of vacation days each year
Embrace parenthood: Minimum of 16 weeks of parental leave, plus generous family formation benefits
Give back your time: 40 hours each year to use toward volunteering with organizations and causes you’re passionate about
Amplify your impact: Double your charitable giving — we match donations up to $1500 USD (or local currency equivalent)

Company HQ

Union Square, San Francisco, CA

Leadership

Shay Banon

(Co-Founder & CTO)

Previously held the position of Technology Director at GigaSpaces Technologies.

Simon Willnauer

(Co-Founder)

Previously spent 13 years at The Apache Software Foundation, holding various positions such as VP Apache Lucene and Lucene Core Commiter and PMC Member.

Uri Boness

(Co-Founder)

Previously worked as a Software Architect and Head of Search at Orange11 for 7 years.

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