Machine Learning Engineer

**POS-P660** * * * **Machine Learning Engineer** **Role Summary** Our mission at HubSpot is to help millions of organizations grow better. We’re looking to hire a Machine Learning Engineer to join our Data & Systems Intelligence (DSI) team. On the DSI team you’ll build machine learning systems that directly support how HubSpot goes to market. As a Machine Learning Engineer, you’ll partner closely with Sales and Customer Success leaders, Data Scientists, and the wider Operations org to turn complex data into scalable, production-ready ML solutions. Your work will influence forecasting, prioritization, and strategic decision-making across GTM teams, with a strong focus on real-world impact and reliability. **What You’ll Do** - Design, build, and deploy ML- and LLM-powered systems, including predictive models, retrieval-augmented generation (RAG) pipelines, and agentic workflows that support GTM decision-making and execution. - Work closely with Sales and Customer Success leaders to translate business questions into ML/AI-powered solutions that drive measurable outcomes. - Apply LLM evaluation techniques (offline evals, golden datasets, human review, and automated metrics) to ensure quality, safety, and business relevance. - Build and maintain LLM infrastructure, including vector stores, embedding pipelines, inference services, and evaluation tooling. - Partner day-to-day with Data Scientists to productionize models, experiments, and analyses into robust, maintainable systems. - Own the end-to-end lifecycle for both classical ML and LLM-based systems, including prompt management, retrieval strategies, tool orchestration, deployment, monitoring, and iteration. - Build and maintain ML pipelines, LLM infrastructure, and tooling that prioritize reliability, performance, and ease of iteration. - Apply techniques such as supervised learning, time-series forecasting, and experimentation to high-impact GTM and operations use cases. - Monitor ML and LLM systems in production, identifying performance drift, bias, or degradation and working with Data Scientists to address issues. - Champion strong MLOps, LLMOps, and AgentOps practices, including reproducibility, observability, documentation, and responsible model usage. - Contribute to shared technical standards and best practices across DSI, Analytics, and GTM-facing data teams. **Required Qualifications** - Professional experience building and deploying machine learning models in production environments. - Strong software engineering skills, with proficiency in Python and experience writing clean, testable, maintainable code. - Experience working with large datasets and data pipelines using SQL and modern data platforms. - Hands-on experience with ML frameworks and libraries (e.g., PyTorch, TensorFlow, scikit-learn) - Experience collaborating closely with Data Scientists to operationalize models and experiments. - Ability to partner with non-technical stakeholders, including Sales and Customer Success leaders, to deliver actionable solutions. - Experience deploying or supporting classic ML and  LLM / generative AI systems in production, including RAG architectures, prompt engineering, LLM evaluation frameworks, and inference optimization. - Experience building or operating agentic systems that combine LLMs with tools, APIs, workflows, or decision logic. - Experience deploying or supporting LLMs / generative AI systems in production, including RAG, LLM Eval frameworks, etc - Operational fluency in Java **Nice-to-Have Qualifications** - Experience supporting go-to-market, revenue, or customer-focused teams with data or ML solutions. - Exposure to time-series forecasting, optimization, or causal inference. - Experience with cloud platforms and ML infrastructure (e.g., AWS, GCP, Kubernetes). - Familiarity with responsible AI practices, including bias detection and governance. - Familiarity with responsible generative AI practices, including prompt safety, hallucination mitigation, and human-in-the-loop review. * * * _We know the_ _[confidence gap](https://www.theatlantic.com/magazine/archive/2014/05/the-confidence-gap/359815/)_ _and_ _[impostor syndrome](https://blog.hubspot.com/marketing/impostor-syndrome-tips)_ _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](https://form.asana.com/?k=Xr9-j19kRaY5T5NjIeyx4Q&d=8587152060687).**_ * * * _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_ * * * _**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](https://www.hubspot.com/careers/diversity)._ _**India** **Applicants:** link to HubSpot India's equal opportunity policy [here](https://drive.google.com/file/d/1fTZ0ht2chl1WRI7Tgrbzh9ytZUhL2jG9/view?__hstc=20629287.8bedd818fefb24c6303ec98fcf9dcfff.1724281309795.1724281309795.1724281309795.1&__hssc=20629287.1.1724281309796&__hsfp=1818362978)._ * * * **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](https://www.hubspot.com/careers/hybrid-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. Explore more: - _[HubSpot Careers](https://www.hubspot.com/careers)_ - _[Life at HubSpot on Instagram](https://www.instagram.com/lifeathubspot)_ * * * _HubSpot may use AI to help screen or assess candidates, but all hiring decisions are always human. More information can be found [here](https://www.hubspot.com/careers/hiring-ai). 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](https://legal.hubspot.com/recruiting-privacy-notice) for details on data processing and your rights._