Principal Machine Learning Engineer @HubSpot
Artificial Intelligence
Salary usd 285,800 - 4..
Remote Location
πŸ‡ΊπŸ‡Έ USA Only
Employment Type full-time
Posted Today

[Hiring] Principal Machine Learning Engineer @HubSpot

Today - HubSpot is hiring a remote Principal Machine Learning Engineer. πŸ’Έ Salary: usd 285,800 - 457,300 per year πŸ“Location: USA

Role Description

The AI Platform Group at HubSpot delivers the ML and AI foundations that enable product teams across the company to create easy, accurate, and consistent AI features for our millions of customers and their customers. This Principal Machine Learning Engineer role will focus on AI Context: building the systems that help HubSpot's AI understand customer, company, activity, and workflow data across the CRM platform.

As a Principal Machine Learning Engineer at HubSpot, you'll help define the technical direction for applied ML and AI systems that transform complex data into customer value. You will work across product, engineering, data, and ML teams to take ambiguous 0-to-1 opportunities through model development, evaluation, productionization, experimentation, and measurable customer or business impact.

We are looking for people who:

  • Have a long track record of delivering high-value, high-impact, cross-team and cross-product projects.
  • Wish to stay hands-on in technical design, model development, production systems, and code while leading by example through collaboration with cross-functional and internal stakeholders.
  • Have a history of developing solutions to ambiguous problems that have had an outsized impact on a large organization's customer experience, product strategy, or business goals.
  • Provide strategic direction and architectural leadership for major ML and AI projects across multiple teams, systems, or product surfaces.
  • Regularly mentor, coach, and teach engineers in their areas of expertise, including helping senior ICs grow through complex technical projects.
  • Demonstrate pragmatic decision-making and problem-solving abilities, including strong judgment around when to use ML, LLMs, retrieval, rules, platform changes, or product changes.
  • Have expert understanding of a range of ML techniques, such as deep learning, optimization, regression, transformers, large language models, transfer learning, retrieval, ranking, recommendations, classification, NLP, and personalization, as well as tools and frameworks such as scikit-learn, PyTorch, TensorFlow, and modern model-serving and evaluation systems.
  • Are expert in crafting the right architecture for a variety of ML and AI Context problems from business requirements, often identifying where ML solutions can be effective in adjacent product areas.
  • Expand analysis beyond offline and online metrics by evaluating privacy, bias, security, reliability, cost, maintainability, model quality, and data governance concerns across the ML lifecycle.
  • Exhibit enthusiasm for building reliable, scalable systems for data processing, feature generation, context retrieval, model training, inference, experimentation, monitoring, and feedback loops.
  • Can guide teams beyond the status quo; we need engineers who lead us beyond what we have and toward what we can build, while creating a shared notion of how to get there.
  • Bring deep expertise in the machine learning concepts behind Applied and Predictive AI, such as recommendation algorithms and systems, binary and multiclass classification, ranking and relevance, semantic retrieval, embeddings, entity understanding, and experimentation.
  • Have experience turning messy, incomplete, or heterogeneous data into useful AI context for customer-facing products, such as customer, company, activity, workflow, conversation, behavioral, CRM, or unstructured document data.
  • Embody our engineering team values.

Qualifications

  • Passionate about leveraging machine learning and AI to transform the way businesses interact with their customers in a collaborative work environment.

Requirements

  • Individual compensation packages are tailored to your skills, experience, qualifications, and other job-related reasons.
  • Annual Cash Compensation Range: $285,800 β€” $457,300 USD.

Benefits

  • Explore the benefits and perks HubSpot offers to help employees grow better.
  • Fair compensation practices focused on transparency with employees, candidates, and community.

Company Description

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.

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.

Before You Apply
️
πŸ‡ΊπŸ‡Έ Be aware of the location restriction for this remote position: USA Only
β€Ό Beware of scams! When applying for jobs, you should NEVER have to pay anything. Learn more.
Principal Machine Learning Engineer @HubSpot
Artificial Intelligence
Salary usd 285,800 - 4..
Remote Location
πŸ‡ΊπŸ‡Έ USA Only
Employment Type full-time
Posted Today
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πŸ‡ΊπŸ‡Έ Be aware of the location restriction for this remote position: USA Only
β€Ό Beware of scams! When applying for jobs, you should NEVER have to pay anything. Learn more.
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