Hubspot is hiring: Senior Machine Learning Engineer II in Cambridge
Hubspot, Cambridge, MA, United States
Senior Machine Learning Engineer II
Engineering
Remote – United Kingdom
POS-31662
Role Summary
HubSpot is building the next generation of AI experiences across our go-to-market products. We’re hiring a
Senior Machine Learning Engineer II
to join the
Flywheel Context (Contacts) team , where you’ll build the
context platform layer
that powers accurate, high-performing AI assistants and agents.
This is a
backend-leaning ML engineering role
focused on
shipping production software
— designing systems that help other engineering teams retrieve relevant facts, manage long/complex context, and evaluate quality at scale. If you love building durable platforms (not just prototypes), this role is for you.
What You’ll Do
Design, build, and operate backend services
that power context retrieval and enrichment for AI assistants and agents.
Build platform capabilities for
storing, searching, and retrieving “insights” and relevant facts
across HubSpot’s GTM data.
Develop systems to
manage and compress context
when it gets large (e.g., long contact histories, high-volume CRM data).
Create tooling that allows other engineering teams to
ship assistants/agents faster , with consistent APIs and reusable primitives.
Build and maintain
evaluation and measurement
approaches (offline evals, golden datasets, automated metrics, human review loops) to ensure context quality and answer accuracy.
Collaborate closely with
sister platform teams and downstream product engineering teams
(your “customers”) to integrate platform capabilities into real experiences.
Own end-to-end delivery:
architecture, implementation, observability, performance, reliability, and iteration .
Required Qualifications
Strong track record
shipping production backend systems
as a senior engineer (ownership from design to delivery).
Professional Java experience
building maintainable, testable services in production (this is core to the role).
Experience implementing
ML workflows in production
(e.g., retrieval/ranking pipelines, feature/data pipelines, model/embedding services, evaluation frameworks).
Comfort working with
data tooling and data-intensive systems
(large datasets, pipelines, and service integrations).
Experience operating software at meaningful scale (e.g., high throughput, significant data volume, performance and reliability constraints).
Strong engineering fundamentals:
system design, code quality, debugging, observability, and operational excellence .
Nice-to-Have Qualifications
Experience with
search/retrieval/relevance/ranking systems
(highly aligned to context work).
Experience with
RAG-style systems , embeddings, vector search, or hybrid retrieval strategies.
Familiarity with
LLM evaluation
patterns (golden sets, automated metrics, human review), hallucination mitigation, and quality measurement.
Experience with distributed systems, event-driven architectures, or stream processing.
Cloud/platform experience (e.g., Kubernetes, AWS/GCP) and running services in production.
Some Python experience (useful, but
not the primary language ).
If you need accommodations or assistance due to a disability, please reach out to us using this form.
Massachusetts Applicants:
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
Germany Applicants:
(m/f/d) - link to HubSpot's Career Diversity page here.
India Applicants:
link to HubSpot India's equal opportunity policy here.
About HubSpot
HubSpot (NYSE: HUBS) is an AI-powered customer platform with all the software, integrations, and resources customers need to connect marketing, sales, and service. HubSpot's connected platform enables businesses to grow faster by focusing on what matters most: customers.
At HubSpot, bold is our baseline. Our employees around the globe move fast, stay customer-obsessed, and win together. Our culture is grounded in four commitments: Solve for the Customer, Be Bold, Learn Fast, Align, Adapt & Go!, and Deliver with HEART. These commitments shape how we work, lead, and grow.
We’re building a company where people can do their best work. We focus on brilliant work, not badge swipes. By combining clarity, ownership, and trust, we create space for big thinking and meaningful progress. And we know that when our employees grow, our customers do too.
Recognized globally for our award-winning culture by Comparably, Glassdoor, Fortune, and more, HubSpot is headquartered in Cambridge, MA, with employees and offices around the world.
HubSpot, Inc. is an equal opportunity employer. As a federal contractor, we take affirmative action to ensure equal opportunity and all candidates are considered without regard to race, color, religion, national origin, age, sex, sexual orientation, gender identity, marital status, ancestry, physical or mental disability, veteran status, or any other legally protected characteristics.
#J-18808-Ljbffr
Engineering
Remote – United Kingdom
POS-31662
Role Summary
HubSpot is building the next generation of AI experiences across our go-to-market products. We’re hiring a
Senior Machine Learning Engineer II
to join the
Flywheel Context (Contacts) team , where you’ll build the
context platform layer
that powers accurate, high-performing AI assistants and agents.
This is a
backend-leaning ML engineering role
focused on
shipping production software
— designing systems that help other engineering teams retrieve relevant facts, manage long/complex context, and evaluate quality at scale. If you love building durable platforms (not just prototypes), this role is for you.
What You’ll Do
Design, build, and operate backend services
that power context retrieval and enrichment for AI assistants and agents.
Build platform capabilities for
storing, searching, and retrieving “insights” and relevant facts
across HubSpot’s GTM data.
Develop systems to
manage and compress context
when it gets large (e.g., long contact histories, high-volume CRM data).
Create tooling that allows other engineering teams to
ship assistants/agents faster , with consistent APIs and reusable primitives.
Build and maintain
evaluation and measurement
approaches (offline evals, golden datasets, automated metrics, human review loops) to ensure context quality and answer accuracy.
Collaborate closely with
sister platform teams and downstream product engineering teams
(your “customers”) to integrate platform capabilities into real experiences.
Own end-to-end delivery:
architecture, implementation, observability, performance, reliability, and iteration .
Required Qualifications
Strong track record
shipping production backend systems
as a senior engineer (ownership from design to delivery).
Professional Java experience
building maintainable, testable services in production (this is core to the role).
Experience implementing
ML workflows in production
(e.g., retrieval/ranking pipelines, feature/data pipelines, model/embedding services, evaluation frameworks).
Comfort working with
data tooling and data-intensive systems
(large datasets, pipelines, and service integrations).
Experience operating software at meaningful scale (e.g., high throughput, significant data volume, performance and reliability constraints).
Strong engineering fundamentals:
system design, code quality, debugging, observability, and operational excellence .
Nice-to-Have Qualifications
Experience with
search/retrieval/relevance/ranking systems
(highly aligned to context work).
Experience with
RAG-style systems , embeddings, vector search, or hybrid retrieval strategies.
Familiarity with
LLM evaluation
patterns (golden sets, automated metrics, human review), hallucination mitigation, and quality measurement.
Experience with distributed systems, event-driven architectures, or stream processing.
Cloud/platform experience (e.g., Kubernetes, AWS/GCP) and running services in production.
Some Python experience (useful, but
not the primary language ).
If you need accommodations or assistance due to a disability, please reach out to us using this form.
Massachusetts Applicants:
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
Germany Applicants:
(m/f/d) - link to HubSpot's Career Diversity page here.
India Applicants:
link to HubSpot India's equal opportunity policy here.
About HubSpot
HubSpot (NYSE: HUBS) is an AI-powered customer platform with all the software, integrations, and resources customers need to connect marketing, sales, and service. HubSpot's connected platform enables businesses to grow faster by focusing on what matters most: customers.
At HubSpot, bold is our baseline. Our employees around the globe move fast, stay customer-obsessed, and win together. Our culture is grounded in four commitments: Solve for the Customer, Be Bold, Learn Fast, Align, Adapt & Go!, and Deliver with HEART. These commitments shape how we work, lead, and grow.
We’re building a company where people can do their best work. We focus on brilliant work, not badge swipes. By combining clarity, ownership, and trust, we create space for big thinking and meaningful progress. And we know that when our employees grow, our customers do too.
Recognized globally for our award-winning culture by Comparably, Glassdoor, Fortune, and more, HubSpot is headquartered in Cambridge, MA, with employees and offices around the world.
HubSpot, Inc. is an equal opportunity employer. As a federal contractor, we take affirmative action to ensure equal opportunity and all candidates are considered without regard to race, color, religion, national origin, age, sex, sexual orientation, gender identity, marital status, ancestry, physical or mental disability, veteran status, or any other legally protected characteristics.
#J-18808-Ljbffr