Principal Machine Learning Engineer

Principal Machine Learning Engineer

Job ID: POS-31344

About HubSpot

HubSpot 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 on four commitments: Solve for the Customer, Be Bold, Learn Fast, Align, Adapt & Go!, and Deliver with HEART.

About the Role

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.

What We're Looking For

• A long track record of delivering high-value, high-impact, cross-team and cross-product projects. Principal MLEs are among the most senior individual contributors at HubSpot; they continually raise the technical bar for the engineering and ML organizations, help shape product vision, and build shared technical direction through strong collaboration and hands-on execution.

• A desire 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.

• 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.

• Ability to provide strategic direction and architectural leadership for major ML and AI projects across multiple teams, systems, or product surfaces.

• Experience regularly mentoring, coaching, and teaching engineers in their areas of expertise, including helping senior ICs grow through complex technical projects.

• Pragmatic decision-making and problem-solving abilities, including strong judgment around when to use ML, LLMs, retrieval, rules, platform changes, or product changes.

• 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.

• Expertise 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.

• Ability to 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.

• Enthusiasm for building reliable, scalable systems for data processing, feature generation, context retrieval, model training, inference, experimentation, monitoring, and feedback loops.

• Capability to 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.

• 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.

• 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.

• Embodiment of HubSpot's engineering team values.

Compensation & Benefits

Annual Cash Compensation Range: $285,800—$457,300 USD

The cash compensation includes base salary, on-target commission for employees in eligible roles, and annual bonus targets under HubSpot's bonus plan for eligible roles. In addition to cash compensation, some roles are eligible to participate in HubSpot's equity plan to receive restricted stock units (RSUs). Some roles may also be eligible for overtime pay. Individual compensation packages are tailored to your skills, experience, qualifications, and other job-related reasons.

Benefits are an important piece of your total compensation package. Explore the benefits and perks HubSpot offers to help employees grow better.

Work Environment

At HubSpot, we value both flexibility and connection. Whether you're a Remote employee or work from the Office, we want you to start your journey here by building strong connections with your team and peers. If you are joining our Engineering team, you will be required to attend a regional HubSpot office for in-person onboarding. If you join our broader Product team, you'll also attend other in-person events, such as your Product Group Summit and other gatherings, to continue building on those connections.

If you require an accommodation due to travel limitations or other reasons, please inform your recruiter during the hiring process. We are committed to supporting candidates who may need alternative arrangements.

Additional Information

We know the confidence gap and impostor syndrome can get in the way of meeting spectacular candidates, so please don't hesitate to apply — we'd love to hear from you.

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.

HubSpot may use AI to help screen or assess candidates, but all hiring decisions are always human. More information can be found here. By submitting your application, you agree that HubSpot may collect your personal data for recruiting, global organization planning, and related purposes. We may use CLEAR ID Verification during the hiring process to confirm your identity and help maintain a safe, secure, and trusted experience for all candidates. Refer to HubSpot's Recruiting Privacy Notice for details on data processing and your rights.