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Staff Software Engineer ML Platform (6244)

Pay
Pay not listedSimilar roles state $118K–$193K
Work setting
Not stated
Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting
Team
Hivemind Enterprise Division › Engineering — team source
Department: Hivemind Enterprise Division › Engineering
From the employer’s posting

Before you apply

Sponsorship
Visa sponsorship not confirmed — sponsorship source
Will you require sponsorship for employment now or in the future?
From the employer’s application form

What you’ll work on

Full posting
  • Build experiment-tracking and model-registry services, including MLflow integrations

  • Connect dataset, code and config versions to training runs, checkpoints and models

  • Develop APIs and adapters for training jobs, data services and artifact storage

  • Make interrupted or failed workflows recoverable with state handling and retries

  • Make checkpoints and model artifacts easy to find and retrieve

From the employer’s posting
Build experiment-tracking and model-registry services, integrating tools such as MLflow where appropriate.
Connect exact dataset, code and configuration versions to training runs, checkpoints and model versions.
Develop APIs and adapters that connect training jobs, data services and artifact storage.
Make interrupted or failed workflows recoverable through reliable state handling, retries and useful diagnostics.
Make checkpoints, model artifacts and evaluation results easy to find and retrieve for further training, evaluation or deployment.

What you’ll bring

All qualifications

Core experience

  • Experience building production backend services for machine-learning platforms or data-intensive workflows.
  • Experience designing APIs, metadata models and persistent state for services used by other engineers.
  • Experience handling storage, partial failures, retries and consistency in distributed systems.
  • Understanding of training runs, checkpoints and model versioning.
  • Ability to work directly with machine-learning users and deliver maintainable software that solves their workflow problems.

Preferred experience

  • Experience with MLflow, Weights & Biases, model registries or comparable experiment-management tools.
  • Experience integrating Kubernetes jobs, object storage or machine-learning workflow systems.
  • Experience with reproducibility, data provenance or evaluation records.
  • Experience supporting open-source software or on-premises and air-gapped deployments.
Qualification wording
Experience building production backend services for machine-learning platforms or data-intensive workflows.
Experience designing APIs, metadata models and persistent state for services used by other engineers.
Experience handling storage, partial failures, retries and consistency in distributed systems.
Understanding of training runs, checkpoints and model versioning.
Ability to work directly with machine-learning users and deliver maintainable software that solves their workflow problems.
Experience with MLflow, Weights & Biases, model registries or comparable experiment-management tools.
Experience integrating Kubernetes jobs, object storage or machine-learning workflow systems.
Experience with reproducibility, data provenance or evaluation records.
Experience supporting open-source software or on-premises and air-gapped deployments.
Apply at Shieldai

Posting record

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Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 5, 2026today
Recorded sightings
1
Employer says posted
Nov 2, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$118K–$193K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 3,721 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 0

Early. Similar jobs usually come down between day 7 and day 56.

From 10,195 similar postings that came down. Coming down is not always a hire.

Shieldai is hiring

22 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Data Scientist hiring is picking up
  • Its jobs tend to stay up a long time
  • 27% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • Kubernetes
  • MLflow
Where the posting names them
- Experience building production backend services for machine-learning platforms or data-intensive workflows. - Strong software engineering skills in Python or a comparable backend language. - Experience designing APIs, metadata models and persistent state for services used by other engineers.
- Experience with MLflow, Weights & Biases, model registries or comparable experiment-management tools. - Experience integrating Kubernetes jobs, object storage or machine-learning workflow systems. - Experience with reproducibility, data provenance or evaluation records.
As a Senior Staff Engineer, you will help build the reference architecture used internally by our engineering teams and delivered to customers building their own AI capabilities. Your work will directly impact how quickly researchers can iterate, how efficiently compute resources are utilized, and how AI systems move from experimentation to operational deployment. This is an opportunity to work at the intersection of modern AI, distributed systems, Kubernetes, and defense, building a platform that enables the next generation of autonomy systems while leveraging the best of the open-source AI ecosystem. #LI-DM2
- - Build experiment-tracking and model-registry services, integrating tools such as MLflow where appropriate. - Connect exact dataset, code and configuration versions to training runs, checkpoints and model versions.
- - Experience with MLflow, Weights & Biases, model registries or comparable experiment-management tools. - Experience integrating Kubernetes jobs, object storage or machine-learning workflow systems.

Your next step

Complete your application on jobs.ashbyhq.com. The employer’s form will show what is required.

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Already applied? Track this application

Has Shieldai posted this job before?

Yes. We’ve followed one other Staff Software Engineer ML Platform (6244) job there since November 2026. It is still up.

  1. San DiegoStill up after 3 days, first seen Nov 2
  2. This jobUp 0 days so far, first seen Nov 5

Demand for Data Scientist roles

New Data Scientist postings at the employers we follow are down 3% over the last 5 weeks compared with the 5 before.

Weekly new Data Scientist postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 1,411, the most 2,973, and the latest week had 1,826.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Scientist, by the work the posting describes.

Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.

Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.

Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.

US government figures for data scientists

Median yearly pay, May 2025
$120,230
Expected change, 2025 to 2035
34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube. 

 

Job Description:

 Model development produces experiments, checkpoints, evaluation results and many versions of the same model. Keeping those records connected lets engineers reproduce results, compare approaches and move a trained model into use. 

We are looking for a Senior Software Engineer to build the backend services that make those workflows reliable. You will connect training runs to their data, code and configuration, manage model artifacts and help machine-learning engineers spend less time reconstructing what happened in an experiment. 

What you'll do:

  • Build experiment-tracking and model-registry services, integrating tools such as MLflow where appropriate. 

  • Connect exact dataset, code and configuration versions to training runs, checkpoints and model versions. 

  • Develop APIs and adapters that connect training jobs, data services and artifact storage. 

  • Make interrupted or failed workflows recoverable through reliable state handling, retries and useful diagnostics. 

  • Make checkpoints, model artifacts and evaluation results easy to find and retrieve for further training, evaluation or deployment. 

  • Work directly with machine-learning engineers to simplify their workflows and reduce manual record keeping. 

  • Deliver tested services with observability and compatible upgrades across supported cloud and customer-managed environments. 

Key Outcomes:

  • Engineers can trace a model version back to the data, code, configuration and run that produced it. 

  • Checkpoints and evaluation evidence remain available when jobs fail or workflows change. 

  • Developers can compare experiments and retrieve model artifacts through consistent APIs. 

  • Teams can reproduce results without manually reconstructing experiment history. 

Required qualifications:

  • Experience building production backend services for machine-learning platforms or data-intensive workflows. 

  • Strong software engineering skills in Python or a comparable backend language. 

  • Experience designing APIs, metadata models and persistent state for services used by other engineers. 

  • Experience handling storage, partial failures, retries and consistency in distributed systems. 

  • Understanding of training runs, checkpoints and model versioning. 

  • Ability to work directly with machine-learning users and deliver maintainable software that solves their workflow problems. 

Preferred qualifications:

  • Experience with MLflow, Weights & Biases, model registries or comparable experiment-management tools. 

  • Experience integrating Kubernetes jobs, object storage or machine-learning workflow systems. 

  • Experience with reproducibility, data provenance or evaluation records. 

  • Experience supporting open-source software or on-premises and air-gapped deployments. 

Why Join Us

  • The AI Factory is the foundation for how Shield AI develops and deploys autonomy.

    As a Senior Staff Engineer, you will help build the reference architecture used internally by our engineering teams and delivered to customers building their own AI capabilities. Your work will directly impact how quickly researchers can iterate, how efficiently compute resources are utilized, and how AI systems move from experimentation to operational deployment.

    This is an opportunity to work at the intersection of modern AI, distributed systems, Kubernetes, and defense, building a platform that enables the next generation of autonomy systems while leveraging the best of the open-source AI ecosystem.

#LI-DM2

#LF

 

Full-time regular employee offer package:

Pay within range listed + Bonus + Benefits + Equity

 

Temporary employee offer package:

Pay within range listed above + temporary benefits package (applicable after 60 days of employment)

 

Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.

 

###

 

Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know. 

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San Diego, California

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