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Data Science Engineer V - US

Pay
Multiple pay amounts — pay source
Partner directly with clinicians and business owners to define and prioritize high-impact problems. 

Our compensation reflects the cost of labor across several geographic markets. The compensation range for this position ranges from $165,830.00/year in our lowest geographic market up to 243,141.80 USD/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. The compensation package may also include incentive compensation opportunities in the form of annual bonus or incentives, equity awards and an Employee Stock Purchase Plan (ESPP). Learn more about benefits at Rackspace.

About Rackspace Technology Rackspace Technology is the trusted operator of the full enterprise AI stack, from governed private cloud to AI inference and agents in production. From edge to core to cloud, we operate the infrastructure, data layer, and software integration to deliver business outcomes with the predictable cost, reliability, security, and compliance that regulated and mission-critical environments demand. We support customers in more than 120 countries with AI capabilities spanning private cloud, public cloud, applications, data and cyber resilience.
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Work setting
Remote — work setting source
Listed location: US-Work from Home
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Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting
  • Architect and own end-to-end delivery of complex statistical/ML and generative AI initiatives

  • Architect and own complex Shiny applications and R-based analytical tools

  • Lead design reviews and set technical direction; mentor junior and mid data scientists

  • Own human-in-the-loop validation for high-stakes models, with clinical SMEs

  • Partner with Research PIs on study design, analysis planning and interpretation

From the employer’s posting
Architect and own end-to-end delivery of complex statistical/ML and generative AI initiatives spanning multiple use cases.
Architect and own delivery of complex Shiny applications and R-based analytical tools spanning multiple use cases.
Lead design reviews and set technical direction for own area; mentor junior/mid data scientists.
Own human-in-the-loop validation processes for high-stakes models within own domain, partnering with clinical SMEs.
Partner directly with Research PIs on study design, analysis planning, and interpretation of complex results.

What you’ll bring

All qualifications

Core experience

  • Bachelor's degree (or higher) in a STEM field, or equivalent experience.
  • Deep experience with responsible-AI evaluation in a pediatric/clinical setting.
  • 6–9 years of experience in data science, with significant project ownership.
  • Experience with fine-tuning or advanced RAG/agentic architectures.
  • 4–6 years hands-on building and productionizing ML/generative AI solutions.
  • Experience running analyses in an HPC or research-computing environment for large-scale or computing intensive studies.
Qualification wording
Bachelor's degree (or higher) in a STEM field, or equivalent experience.
Deep experience with responsible-AI evaluation in a pediatric/clinical setting.
6–9 years of experience in data science, with significant project ownership.
Experience with fine-tuning or advanced RAG/agentic architectures.
4–6 years hands-on building and productionizing ML/generative AI solutions.
Experience running analyses in an HPC or research-computing environment for large-scale or computing intensive studies.
Education & alternatives
Required Education & Experience - Bachelor's degree (or higher) in a STEM field, or equivalent experience. - 6–9 years of experience in data science, with significant project ownership.
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Posting record

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Status in our records
Live
First seen by us
Oct 5, 202630 days ago
Recorded sightings
26
Last seen by us
Nov 4, 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

$166K–$240K is typical

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

From 1,279 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 30

Similar jobs usually come down between day 6 and day 69.

At Rackspace, jobs usually come down by about day 26.

From 4,423 similar postings that came down, and 11 of Rackspace’s. Coming down is not always a hire.

Rackspace is hiring

4 open jobs

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

  • Takes jobs down quickly
Hiring record

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  • R
Where the posting names them
- 4–6 years hands-on building and productionizing ML/generative AI solutions. - 4–6 years hands-on experience with R, RStudio, and Shiny application development, including production-grade interactive tools. - 1+ year informally mentoring data scientists.
- Advanced expertise in statistics, ML, and data mining; independently designs model architectures and evaluation frameworks. - Advanced expertise in R and RStudio; independently designs and architects production-grade Shiny applications. - Deep understanding of generative AI/LLM architecture; independently designs RAG/agentic solutions for high-stakes clinical/operational use cases.

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About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

Summary: Owns complex, cross-cutting statistical/ML and generative AI initiatives that solve high-impact clinical and business problems, setting technical direction for the area, mentoring data scientists, and partnering directly with clinical and business leaders. 


Required Education & Experience 

  • Bachelor's degree (or higher) in a STEM field, or equivalent experience. 
  • 6–9 years of experience in data science, with significant project ownership. 
  • 4–6 years hands-on building and productionizing ML/generative AI solutions. 
  • 4–6 years hands-on experience with R, RStudio, and Shiny application development, including production-grade interactive tools. 
  • 1+ year informally mentoring data scientists. 

Preferred 

  • Deep experience with responsible-AI evaluation in a pediatric/clinical setting. 
  • Experience with fine-tuning or advanced RAG/agentic architectures. 
  • Experience running analyses in an HPC or research-computing environment for large-scale or computing intensive studies. 
  • Established working relationships with Research PIs, including study-design or analysis-planning input. 

Knowledge, Skills, and Abilities 

  • Advanced expertise in statistics, ML, and data mining; independently designs model architectures and evaluation frameworks. 
  • Advanced expertise in R and RStudio; independently designs and architects production-grade Shiny applications. 
  • Deep understanding of generative AI/LLM architecture; independently designs RAG/agentic solutions for high-stakes clinical/operational use cases. 
  • Deep understanding of HPC/research-computing workflows; independently determines when compute-intensive work warrants HPC resources. 
  • Independently designs bias/safety evaluation frameworks, with rigorous scrutiny for pediatric populations. 
  • Mentors mid-level and junior data scientists on modeling, R/Shiny best practices, and responsible-AI practices. 
  • Occasionally presents technical work to cross-functional groups of 5–10 people. 

Job Functions 

  • Architect and own end-to-end delivery of complex statistical/ML and generative AI initiatives spanning multiple use cases. 
  • Architect and own delivery of complex Shiny applications and R-based analytical tools spanning multiple use cases. 
  • Lead design reviews and set technical direction for own area; mentor junior/mid data scientists. 
  • Own human-in-the-loop validation processes for high-stakes models within own domain, partnering with clinical SMEs. 
  • Own bias/safety/explainability evaluation for owned AI outputs, with particular attention to pediatric-population risk. 
  • Partner directly with Research PIs on study design, analysis planning, and interpretation of complex results. 
  • Advise on appropriate use of HPC/research-computing resources for compute-intensive modeling work. 
  • Build tools/libraries that scale data science products across multiple teams. 
  • Partner directly with clinicians and business owners to define and prioritize high-impact problems. 


Our compensation reflects the cost of labor across several geographic markets. The compensation range for this position ranges from $165,830.00/year in our lowest geographic market up to 243,141.80 USD/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. The compensation package may also include incentive compensation opportunities in the form of annual bonus or incentives, equity awards and an Employee Stock Purchase Plan (ESPP). Learn more about benefits at Rackspace.



About Rackspace Technology

Rackspace Technology is the trusted operator of the full enterprise AI stack, from governed private cloud to AI inference and agents in production. From edge to core to cloud, we operate the infrastructure, data layer, and software integration to deliver business outcomes with the predictable cost, reliability, security, and compliance that regulated and mission-critical environments demand. We support customers in more than 120 countries with AI capabilities spanning private cloud, public cloud, applications, data and cyber resilience.


More on Rackspace Technology

Though we’re all different, Rackers thrive through our connection to a central goal: to be a valued member of a winning team on an inspiring mission. We bring our whole selves to work every day. And we embrace the notion that unique perspectives fuel innovation and enable us to best serve our customers and communities around the globe. We welcome you to apply today and want you to know that we are committed to offering equal employment opportunity without regard to age, color, disability, gender reassignment or identity or expression, genetic information, marital or civil partner status, pregnancy or maternity status, military or veteran status, nationality, ethnic or national origin, race, religion or belief, sexual orientation, or any legally protected characteristic. If you have a disability or special need that requires accommodation, please let us know.

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