Principal Machine Learning Engineer – AI Context

🕒 July 24

🇺🇸 United States – Remote

💵 $313k - $500k / year

⏰ Full Time

🔴 Lead

🤖 AI Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 24%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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HubSpot

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2006

🤝 B2B

☁️ SaaS

📣 Marketing

B2B • SaaS • Marketing

HubSpot is an AI-powered customer platform that combines marketing, sales, and customer service software into one integrated suite. With over 238,000 customers in 135 countries, HubSpot offers tools for marketing automation, sales management, customer service, content marketing, operations, and B2B commerce. With products like Marketing Hub, Sales Hub, Service Hub, and Content Hub, HubSpot enables businesses to generate leads, close deals, and provide excellent customer support, all while using AI to enhance operations and insights. The platform is designed to unify teams and customer data, supporting both small startups and large enterprises in their growth journey.

📋 Description

• Define the technical direction for applied ML and AI systems that transform complex data into customer value • Build AI Context systems that help HubSpot’s AI understand customer, company, activity, and workflow data across the CRM platform • Lead ambiguous 0-to-1 opportunities through model development, evaluation, productionization, experimentation, and measurable customer or business impact • Provide strategic direction and architectural leadership for major ML and AI projects across multiple teams, systems, or product surfaces • Collaborate across product, engineering, data, and ML teams • Mentor, coach, and teach engineers, including helping senior individual contributors grow through complex technical projects • Build reliable, scalable systems for data processing, feature generation, context retrieval, model training, inference, experimentation, monitoring, and feedback loops • Guide teams beyond the status quo and establish shared technical direction • Evaluate privacy, bias, security, reliability, cost, maintainability, model quality, and data governance across the ML lifecycle

🎯 Requirements

• Long track record of delivering high-value, high-impact, cross-team and cross-product projects • Experience leading technical design, model development, production systems, and code through collaboration with cross-functional and internal stakeholders • History of developing solutions to ambiguous problems with outsized impact on customer experience, product strategy, or business goals • Strategic direction and architectural leadership for major ML and AI projects across multiple teams, systems, or product surfaces • Experience mentoring, coaching, and teaching engineers, including senior individual contributors • Pragmatic decision-making and strong problem-solving abilities • Expert understanding of deep learning, optimization, regression, transformers, large language models, transfer learning, retrieval, ranking, recommendations, classification, NLP, and personalization • Expertise with scikit-learn, PyTorch, TensorFlow, and modern model-serving and evaluation systems • Expertise crafting architectures for ML and AI Context problems from business requirements • Ability to evaluate privacy, bias, security, reliability, cost, maintainability, model quality, and data governance across the ML lifecycle • Deep expertise in 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 • Embody HubSpot engineering team values

🏖️ Benefits

• Remote work arrangement • In-person regional office onboarding for Engineering employees • In-person Product Group Summit and other gatherings for broader Product team employees • Alternative arrangements for candidates with travel limitations or other accommodation needs • Disability accommodations and assistance during the application process