<div class="content-intro"><p>The GitLab&nbsp;<a class="c-link" href="https://about.gitlab.com/solutions/devops-platform/" target="_blank" data-stringify-link="https://about.gitlab.com/solutions/devops-platform/" data-sk="tooltip_parent" data-remove-tab-index="true">DevSecOps platform</a>&nbsp;empowers 100,000+ organizations to deliver software faster and more efficiently. We are one of the&nbsp;<a class="c-link" href="https://about.gitlab.com/company/culture/all-remote/guide/" target="_blank" data-stringify-link="https://about.gitlab.com/company/culture/all-remote/guide/" data-sk="tooltip_parent" data-remove-tab-index="true">world’s largest all-remote companies</a>&nbsp;with 2,000+ team members and&nbsp;<a class="c-link" href="https://handbook.gitlab.com/handbook/values/" target="_blank" data-stringify-link="https://about.gitlab.com/handbook/values/" data-sk="tooltip_parent" data-remove-tab-index="true">values</a>&nbsp;that foster a culture where people embrace the belief that everyone can contribute. Learn more about&nbsp;<a class="c-link" href="https://vimeo.com/778157354" target="_blank" data-stringify-link="https://vimeo.com/778157354" data-sk="tooltip_parent" data-remove-tab-index="true">Life at GitLab</a>.</p></div><h4 style="text-align: justify;"><strong>About the work&nbsp;</strong></h4>
<p style="text-align: justify;">This group is focused on enabling GitLab users to build and run data science workloads across&nbsp;<a href="https://about.gitlab.com/platform/">GitLab’s AI-powered DevSecOps platform</a>. This individual will play a key role in building features that aid in the expansion of GitLab’s <a href="https://handbook.gitlab.com/handbook/product/personas/#list-of-user-personas">core personas</a> to address the needs of data science teams and will work cross-functionally with <a href="https://about.gitlab.com/handbook/product/categories/#devops-stages">other GitLab stages</a> to ensure our platform supports ML/AI workloads that align with our <a href="https://about.gitlab.com/direction/modelops/">ModelOps product direction</a>. This individual will be responsible for enhancing existing product features used by millions of users across the world.<br><br>Your role will be to build, scale, and iterate on ML features that help operationalize customers’ ML ( Both AI and Gen AI solutions )&nbsp; and aid in dropping the costs of Machine Learning. You will balance short and long-term efforts from a feature perspective and work on backend machine learning enterprise feature challenges. With the team, you will be building the backbone of our ML efforts that solve the challenges of today and tomorrow for our customers building in the journey of ML.</p>
<p style="text-align: justify;">&nbsp;Some examples:</p>
<ul style="text-align: justify;">
<li>MLOps features in <a href="https://learn.gitlab.com/mlops/mlops-tech-demo">GitLab DevSecops Platform&nbsp;</a></li>
<li><a href="https://www.youtube.com/watch?v=tU-iu02pYXo">GitLab Model Registry&nbsp;</a></li>
</ul>
<h4 style="text-align: justify;"><strong>What you will do</strong></h4>
<ul style="text-align: justify;">
<li>Play a key role in the design, implementation, building and integration of product features;</li>
<li>Solve technical backend machine learning&nbsp; problems of high scope and complexity;</li>
<li>Test, deploy, maintain, and improve ML system solution features that aid with registry, deployments, inference of models;</li>
<li>Help to define and improve our internal standards for style, maintainability, and best practices for a high-scale web environment;</li>
<li>Collaborate with other ML, Python, Ruby, Golang engineers to build GenAI Solutions</li>
</ul>
<h4 style="text-align: justify;"><strong>What you will bring&nbsp;</strong></h4>
<ul style="text-align: justify;">
<li>Significant experience in Golang</li>
<li>Some level of python is preferred</li>
<li>Some level of Vue.Js is preferred</li>
<li>Significant experience in how to operationalize the lifecycle management of data science workloads, including data ingestion and ETL, feature engineering, development environment setup, CI/CD integration, model versioning, testing, and production deployment</li>
<li>Deep technical understanding and usability&nbsp; of ML/AI technologies (e.g GPUs, model inference, training, natural language processing, large language models, embeddings, vector database, etc)</li>
<li>Production experience with Terraform, Kubernetes, Docker, and preferably GCP or equivalent technologies.</li>
<li>Experience with inference backend and post-production monitoring of large language models ( &gt;10GB)</li>
<li>High interest in defining experimentation and agent architecture for large-scale ML recommendation engines&nbsp;</li>
<li>A genuine passion for learning as you will be solving the challenges of today, tomorrow, and many years to come.</li>
</ul>
<h4 style="text-align: justify;"><strong>About the team</strong></h4>
<p style="text-align: justify;">Today, data scientists piece together data, tooling, and frameworks to get bespoke data science workloads running and producing business value. Data scientists then hand off models to engineering teams to attempt to deploy them to production. These teams speak different languages, use different tools, and have completely different workflows. This makes it very difficult to deploy data science workloads to production, increasing time to value and costs. One of our primary goals for our ModelOps stage is to reduce the complexities of data science workloads and integrate these workloads to easily be managed and developed within GitLab.</p>
<h4 style="text-align: justify;"><strong>How GitLab will support you</strong></h4>
<ul style="text-align: justify;">
<li>All remote, <a href="https://about.gitlab.com/company/culture/all-remote/asynchronous/">asynchronous</a> work environment</li>
<li><a href="https://about.gitlab.com/handbook/paid-time-off/">Unlimited PTO</a> (paid time off)</li>
<li>GitLab is home to many dedicated Team Member Resource Groups</li>
<li>Benefits to manage your health, wealth, and well-being regardless of location</li>
<li>Equity compensation &amp; Employee Stock Purchase Plan offered</li>
<li>A personal <a href="https://about.gitlab.com/handbook/total-rewards/benefits/general-and-entity-benefits/#parental-leave">growth and development budget </a>per year</li>
<li><a href="https://about.gitlab.com/handbook/total-rewards/benefits/general-and-entity-benefits/#parental-leave">Parental leave</a>: 16 weeks</li>
<li><a href="https://about.gitlab.com/handbook/finance/procurement/office-equipment-supplies/">Home office</a> support</li>
</ul>
<p style="text-align: justify;">&nbsp;</p>
<p style="text-align: justify;"><em>Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application.</em></p><div class="content-conclusion"><hr>
<p><strong>Country Hiring Guidelines: </strong>GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process.&nbsp;&nbsp;</p>
<p><strong>Privacy Policy: </strong>Please review our <a href="https://about.gitlab.com/handbook/hiring/candidate/faq/recruitment-privacy-policy/" target="_blank">Recruitment Privacy Policy.</a> Your privacy is important to us.</p>
<p>GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also&nbsp;<a href="https://about.gitlab.com/handbook/people-policies/inc-usa/#equal-employment-opportunity-policy" target="_blank">GitLab’s EEO Policy</a>&nbsp;and&nbsp;<a href="https://about.gitlab.com/handbook/labor-and-employment-notices/#eeoc-us-equal-employment-opportunity-commission-notices" target="_blank">EEO is the Law</a>. If you have a disability or special need that requires&nbsp;<a href="https://about.gitlab.com/handbook/people-policies/inc-usa/#reasonable-accommodation" target="_blank">accommodation</a>, please let us know during the&nbsp;<a href="https://about.gitlab.com/handbook/hiring/interviewing/#adjustments-to-our-interview-process" target="_blank">recruiting process</a>.</p></div>

The GitLab [DevSecOps platform](https://about.gitlab.com/solutions/devops-
platform/) empowers 100,000+ organizations to deliver software faster and more
efficiently. We are one of the [world’s largest all-remote
companies](https://about.gitlab.com/company/culture/all-remote/guide/) with
2,000+ team members and [values](https://handbook.gitlab.com/handbook/values/)
that foster a culture where people embrace the belief that everyone can
contribute. Learn more about [Life at GitLab](https://vimeo.com/778157354).

####  **About the work  **

This group is focused on enabling GitLab users to build and run data science
workloads across [GitLab’s AI-powered DevSecOps
platform](https://about.gitlab.com/platform/). This individual will play a key
role in building features that aid in the expansion of GitLab’s [core
personas](https://handbook.gitlab.com/handbook/product/personas/#list-of-user-
personas) to address the needs of data science teams and will work cross-
functionally with [other GitLab
stages](https://about.gitlab.com/handbook/product/categories/#devops-stages)
to ensure our platform supports ML/AI workloads that align with our [ModelOps
product direction](https://about.gitlab.com/direction/modelops/). This
individual will be responsible for enhancing existing product features used by
millions of users across the world.  
  
Your role will be to build, scale, and iterate on ML features that help
operationalize customers’ ML ( Both AI and Gen AI solutions )  and aid in
dropping the costs of Machine Learning. You will balance short and long-term
efforts from a feature perspective and work on backend machine learning
enterprise feature challenges. With the team, you will be building the
backbone of our ML efforts that solve the challenges of today and tomorrow for
our customers building in the journey of ML.

 Some examples:

  * MLOps features in [GitLab DevSecops Platform ](https://learn.gitlab.com/mlops/mlops-tech-demo)
  * [GitLab Model Registry ](https://www.youtube.com/watch?v=tU-iu02pYXo)

#### **What you will do**

  * Play a key role in the design, implementation, building and integration of product features;
  * Solve technical backend machine learning  problems of high scope and complexity;
  * Test, deploy, maintain, and improve ML system solution features that aid with registry, deployments, inference of models;
  * Help to define and improve our internal standards for style, maintainability, and best practices for a high-scale web environment;
  * Collaborate with other ML, Python, Ruby, Golang engineers to build GenAI Solutions

#### **What you will bring  **

  * Significant experience in Golang
  * Some level of python is preferred
  * Some level of Vue.Js is preferred
  * Significant experience in how to operationalize the lifecycle management of data science workloads, including data ingestion and ETL, feature engineering, development environment setup, CI/CD integration, model versioning, testing, and production deployment
  * Deep technical understanding and usability  of ML/AI technologies (e.g GPUs, model inference, training, natural language processing, large language models, embeddings, vector database, etc)
  * Production experience with Terraform, Kubernetes, Docker, and preferably GCP or equivalent technologies.
  * Experience with inference backend and post-production monitoring of large language models ( >10GB)
  * High interest in defining experimentation and agent architecture for large-scale ML recommendation engines 
  * A genuine passion for learning as you will be solving the challenges of today, tomorrow, and many years to come.

#### **About the team**

Today, data scientists piece together data, tooling, and frameworks to get
bespoke data science workloads running and producing business value. Data
scientists then hand off models to engineering teams to attempt to deploy them
to production. These teams speak different languages, use different tools, and
have completely different workflows. This makes it very difficult to deploy
data science workloads to production, increasing time to value and costs. One
of our primary goals for our ModelOps stage is to reduce the complexities of
data science workloads and integrate these workloads to easily be managed and
developed within GitLab.

#### **How GitLab will support you**

  * All remote, [asynchronous](https://about.gitlab.com/company/culture/all-remote/asynchronous/) work environment
  * [Unlimited PTO](https://about.gitlab.com/handbook/paid-time-off/) (paid time off)
  * GitLab is home to many dedicated Team Member Resource Groups
  * Benefits to manage your health, wealth, and well-being regardless of location
  * Equity compensation & Employee Stock Purchase Plan offered
  * A personal [growth and development budget ](https://about.gitlab.com/handbook/total-rewards/benefits/general-and-entity-benefits/#parental-leave)per year
  * [Parental leave](https://about.gitlab.com/handbook/total-rewards/benefits/general-and-entity-benefits/#parental-leave): 16 weeks
  * [Home office](https://about.gitlab.com/handbook/finance/procurement/office-equipment-supplies/) support



_Please note that we welcome interest from candidates with varying levels of
experience; many successful candidates do not meet every single requirement.
Additionally, studies have shown that people from underrepresented groups are
less likely to apply to a job unless they meet every single qualification. If
you're excited about this role, please apply and allow our recruiters to
assess your application._

* * *

**Country Hiring Guidelines:** GitLab hires new team members in countries
around the world. All of our roles are remote, however some roles may carry
specific location-based eligibility requirements. Our Talent Acquisition team
can help answer any questions about location after starting the recruiting
process.  

**Privacy Policy:** Please review our [Recruitment Privacy
Policy.](https://about.gitlab.com/handbook/hiring/candidate/faq/recruitment-
privacy-policy/) Your privacy is important to us.

GitLab is proud to be an equal opportunity workplace and is an affirmative
action employer. GitLab’s policies and practices relating to recruitment,
employment, career development and advancement, promotion, and retirement are
based solely on merit, regardless of race, color, religion, ancestry, sex
(including pregnancy, lactation, sexual orientation, gender identity, or
gender expression), national origin, age, citizenship, marital status, mental
or physical disability, genetic information (including family medical
history), discharge status from the military, protected veteran status (which
includes disabled veterans, recently separated veterans, active duty wartime
or campaign badge veterans, and Armed Forces service medal veterans), or any
other basis protected by law. GitLab will not tolerate discrimination or
harassment based on any of these characteristics. See also [GitLab’s EEO
Policy](https://about.gitlab.com/handbook/people-policies/inc-usa/#equal-
employment-opportunity-policy) and [EEO is the
Law](https://about.gitlab.com/handbook/labor-and-employment-notices/#eeoc-us-
equal-employment-opportunity-commission-notices). If you have a disability or
special need that requires
[accommodation](https://about.gitlab.com/handbook/people-policies/inc-
usa/#reasonable-accommodation), please let us know during the [recruiting
process](https://about.gitlab.com/handbook/hiring/interviewing/#adjustments-
to-our-interview-process).

