Senior MLOps Engineer, Elastic

$133.1-252.9k

This role is currently eligible to participate in Elastic's stock program. Salary applies to Seattle WA, Los Angeles CA, the San Francisco Bay Area CA, and the New York City Metro Area

AWS

Kubernetes

GCP

Python

Airflow

Senior and Expert level

Remote from Canada, US

Open source platform powering search, observability, security, and more

Job no longer available

Open source platform powering search, observability, security, and more

1001+ employees

B2BAnalyticsSaaS

Job no longer available

$133.1-252.9k

This role is currently eligible to participate in Elastic's stock program. Salary applies to Seattle WA, Los Angeles CA, the San Francisco Bay Area CA, and the New York City Metro Area

AWS

Kubernetes

GCP

Python

Airflow

Senior and Expert level

Remote from Canada, US

1001+ employees

B2BAnalyticsSaaS

Company mission

To help turn endless data possibilities into real results with the power of Search AI.

Job

Company

Role

Who you are

Be comfortable working in a fully-remote environment
Be able to communicate clearly to diverse groups of stakeholders coming from different disciplines, time zones, and programming language preferences
Proficient Python programming skills
Experience with writing and running tests (unit tests, integration tests, regression tests)
Experience with AWS or GCP
Experience with Airflow, Buildkite, or other CICD tooling
Experience with performing data analysis as required to support data quality decisions
Ability to both give and receive helpful code reviews
If you are passionate about ML and Data Science and would like to apply your expertise to secure the world's data from attacks, we would love to have you join our growing team!

Desirable

Experience in Security
Experience with Kubernetes
Working knowledge of deep learning, clustering, and/or graph algorithms
Experience designing, training, and evaluating models using popular ML frameworks

What the job involves

Elastic Security focuses on AI-driven Security solutions across our SIEM and Endpoint products
The Security ML team researches, designs, and builds AI and ML solutions and drives innovation in this domain
We are looking for a Senior MLOps Engineer to join our ML team and continue to innovate, build, and ship new models that will help secure our users against the latest emerging threats
You will collaborate with the broader Elastic Security team, which consists of a diverse group of skilled researchers, ML engineers, data scientists, and developers who possess extensive domain expertise in their respective areas
Support ongoing efforts to improve data quality and ML model training automation, as well as observability and reproducibility of ML models
Collaborate within the Data Science team, and with members of other teams, especially Data Engineering
Promote long-term vision for monitoring performance of deployed models to identify concept drift and determine retraining cadence
Determine how to improve models over time by leveraging implicit and explicit feedback

Our take

Organizations are dealing with exploding data volumes increasingly sophisticated cyber threats, and the growing expectation tha ttechnology should help act on problems, not just report them. Ai is moving from experimentation into real operations, especially in security and observability where speed and context are critical. So now, both enterprises and governments are looking for simpler, shared platforms that sale easily and reduce complexity rather than add to it.

And Elastic sits at the intersection of these needs with its Search AI Platform that helps organizations turn large amounts of structured and unstructured data into clear insights and actiontions across search, security, and observability. Elastic's strength lies in its open, flexible approach, which breaks down data silos and provides a context people and AI systems need to make daster, better decisions. The goal is straightforward: help teams see what's happening, understand it quickly, and respond confidently.

Recently, the company worked with CISA to deliver a unified, cloud-based SIEM for US federal agencies, this highlights strong trust in Elastic's security and scalability. Alongside this, its AWS Agentic AI Specialization also reflects leadership in making autonomous AI system practical and reliable. Together, these milestones position Elastic well for the future, as organizations increasingly rely on shared platforms and intelligent systems to manage ris, complexity, and growth.

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

Ashutosh Kulkarni

(CEO)

Ashutosh joined Elastic in 2021 as CPO, becoming CEO in 2022. Prior to this, he was an EVP and CPO of Enterprise at McAfee, a Senior VP and GM of Web Performance and Web Security at Akamai Technologies, and a Senior VP and GM of Informatica Cloud at Informatica.

Shay Banon

(Co-Founder & CTO)

Shay co-founded Elastic in 2012 and has served as the CTO since.

Navam Welihinda

(CFO)

Prior to joining Elastic in 2025, Navam was the CFO at Grammarly. He also spent nearly 8 years at HashiCorp as VP of Finance and CFO and was the Head of Finance, Compose at IBM for 1 year.

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