Staff Backend Engineer, Customer Value Optimisation

HelloFresh

New York, US

Who this role is best for

Aimed at mid-level backend engineers with ML model serving experience who thrive at the intersection of data science and engineering.

Best fit for

Engineers who excel as technical bridges between data science and backend teams.
— “technical bridge that turns ML models into reliable, scalable production systems”
Candidates with a track record of scaling ML model serving systems.
— “building and operating ML model serving systems or ML platforms in production”
Those comfortable leading cross-squad technical initiatives without direct reports.
— “Lead cross-squad technical initiatives, from architecture decisions to hands-on implementation”

Things to consider

Role requires fluency in Python and distributed systems architecture.
— “strong foundation in Python”
Expectation to mentor engineers across squads without formal authority.
— “Mentor and support engineers across squads without direct line management responsibility”

How to stand out

Demonstrate cross-functional collaboration with data science teams.
— “working fluently with Data Scientists, Machine Learning Engineers, and Data Engineers”
Showcase contributions to engineering standards and technical roadmaps.
— “Contribute to tribe-wide engineering standards and shape the technical roadmap”

Pace · SteadyCollaboration · HighAutonomy · MediumDecision Impact · TeamLevel · Mid Level

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

design and build robust infrastructure for ML models
translate Data Science needs into engineering solutions
define best practices for model serving

Typical background

7+ years of backend engineering experienceproven experience in ML model serving

Skills & requirements

Required

Backend EngineeringML Model ServingDistributed SystemsAPI DesignMicroservices Architecture

Preferred

ML FrameworksFeature StoresModel RegistriesMlops ToolingE-commerce

Stack & domain

Backend EngineeringPythonMl ModelsDistributed SystemsApisMicroservices ArchitectureMl FrameworksServing ToolsFeature StoresModel RegistriesMlops ToolingE-commerceSubscriptionPersonalization DomainsLeadershipCommunicationTeamworkProblem SolvingMLData Science

About the role

Original posting from HelloFresh

The Role
We're looking for a Staff Backend Engineer to join our Customer Value Optimization (CVO) tribe at HelloFresh. This is a high-impact individual contributor role sitting at the intersection of Data Science and Backend Engineering — you'll be the technical bridge that turns ML models into reliable, scalable production systems.
You'll work across squads within the CVO tribe, partnering closely with Data Scientists and Backend Engineers to define how we serve ML models at scale, raise the technical bar, and accelerate the tribe's ability to deliver value to our customers.
What you’ll do
Design, build, and own robust, scalable infrastructure for live serving of ML models in production
Act as the technical bridge between Data Science and Backend Engineering teams within the CVO tribe — translating DS needs into scalable engineering solutions
Define and drive best practices for model serving, APIs, and system design across squads
Lead cross-squad technical initiatives, from architecture decisions to hands-on implementation
Partner with Data Scientists to ensure models are production-ready — performant, observable, and maintainable
Contribute to tribe-wide engineering standards and shape the technical roadmap
Mentor and support engineers across squads without direct line management responsibility
What you’ll bring
7+ years of backend engineering experience, with a strong foundation in Python
Proven experience building and operating ML model serving systems or ML platforms in production
Deep understanding of distributed systems, APIs, and microservices architecture
Strong track record of working across team boundaries to deliver complex, cross-functional projects
Excellent communication skills — able to work fluently with Data Scientists, Machine Learning Engineers, and Data Engineers
A collaborative, low-ego approach with strong technical judgment
Nice to Have
Experience with ML frameworks and serving tools
Familiarity with feature stores, model registries, or MLOps tooling
Background in e-commerce, subscription, or personalization domains
New York Pay Range$156,800—$261,300 USDColorado Pay Range$146,600—$244,300 USD

Source: HelloFresh careers