Senior Machine Learning Engineer

POS-29423

 HubSpot, a market leader in sales and marketing technology, is the preferred platform for scaling businesses. The Finance Data team’s Advanced Analytics and Insights (AAI) group is pioneering the use of machine learning, large language models (LLMs), and intelligent agents to unlock high-impact financial insights. As we grow, we’re seeking an experienced Senior Machine Learning Engineer to build out the foundational AI and ML systems that support  complex AI needs from forecasting, smart insights to finance-focused copilots.

As a Senior Machine Learning  Engineer (MLE) on the newly formed Finance AAI team,  you’ll build production-grade machine learning systems, deploy LLM-powered tools, and set up the ML infrastructure that supports financial forecasting, risk analysis, and AI-driven insights.. This is a role for builders: engineers who love solving complex problems and enabling business impact through smart automation. Strong coding skills in Python, ML, Gen-AI domains are very essential. Experience with Java is a strong plus that will help navigate our internal systems.

Responsibilities & Role Expectations

• Collaborate with data scientists to deploy and maintain machine learning models for forecasting, anomaly detection, NLP analysis and customer outcome prediction. Take ownership of the full development lifecycle : including development, CI/CD pipelines, containerization, orchestration, and performance monitoring with tools like MLflow.
• Build a strong foundation of scalable and reusable infrastructure to support Finance’s ML/AI experimentation. Contribute SDKs, APIs, and clear documentation to streamline ML/LLM adoption and provide shared services in line with the Finance AAI’s roadmap.
• Design and implement LLM-driven workflows and autonomous agents tailored to Finance use cases such as narrative generation, AI copilots, and RAG-based insights. Apply techniques like prompt engineering, fine-tuning, and embedding search using open-source libraries including LangChain, Hugging Face, and OpenAI APIs. Confidently validate model performance using standard benchmarks and custom metrics.
• Champion strong engineering practices through mentorship and technical guidance, ensuring systems are aligned with data governance and regulatory standards. Collaborate with central teams at Hubspot to enable ML/AI best practices
• Engage in code reviews, testing, and documentation efforts to uphold code quality and maintainability. Mentor junior engineers and data scientists to strengthen their software development skills, optimize algorithms, and stay current with advancements in the field.

About You

• Degree in Computer Science, Statistics, Applied Mathematics, or a related quantitative field.
• Expert knowledge of machine learning and AI techniques, with a strong track record of selecting appropriate methods and successfully deploying multiple models in production, including full lifecycle ownership, development, CI/CD, monitoring, and maintenance
• Strong Python & SQL skills with deep experience in ML/AI libraries such as scikit-learn, TensorFlow, PyTorch, Hugging Face, CrewAI and LangChain.
• Hands-on experience with LLM deployment (workflows & agents), vector search, and RAG pipelines at scale.
• Familiarity with Java is a big plus, especially for internal service integration.
• Knowledgeable in model monitoring, alerting, and evaluation techniques.
• Proficient developing & working with API’s & standard ML deployment stack: Git, Docker, Kubernetes, FastAPI, etc.
• Capable of independently leading ML/AI projects from concept to production.
• Excellent communicator, able to translate complex technical ideas to diverse audiences. Collaborative and creative, thrives in fast-paced, iterative environments.

Bonus Points

• Familiarity with React framework, and RPC functions to expose back-end systems to front-end clients.
• Experience working with Kafka or other stream based processing architecture.
• Familiarity with emerging LLM architectures and techniques in LLM space like Graph RAG, MCP, A2A, Long/Short term memory.

Cash compensation range: 136000-204000 USD Annually

 HubSpot, a market leader in sales and marketing technology, is the preferred platform for scaling businesses. The Finance Data team’s Advanced Analytics and Insights (AAI) group is pioneering the use of machine learning, large language models (LLMs), and intelligent agents to unlock high-impact financial insights. As we grow, we’re seeking an experienced Senior Machine Learning Engineer to build out the foundational AI and ML systems that support  complex AI needs from forecasting, smart insights to finance-focused copilots.

As a Senior Machine Learning  Engineer (MLE) on the newly formed Finance AAI team,  you’ll build production-grade machine learning systems, deploy LLM-powered tools, and set up the ML infrastructure that supports financial forecasting, risk analysis, and AI-driven insights.. This is a role for builders: engineers who love solving complex problems and enabling business impact through smart automation. Strong coding skills in Python, ML, Gen-AI domains are very essential. Experience with Java is a strong plus that will help navigate our internal systems.

Responsibilities & Role Expectations

• Collaborate with data scientists to deploy and maintain machine learning models for forecasting, anomaly detection, NLP analysis and customer outcome prediction. Take ownership of the full development lifecycle : including development, CI/CD pipelines, containerization, orchestration, and performance monitoring with tools like MLflow.
• Build a strong foundation of scalable and reusable infrastructure to support Finance’s ML/AI experimentation. Contribute SDKs, APIs, and clear documentation to streamline ML/LLM adoption and provide shared services in line with the Finance AAI’s roadmap.
• Design and implement LLM-driven workflows and autonomous agents tailored to Finance use cases such as narrative generation, AI copilots, and RAG-based insights. Apply techniques like prompt engineering, fine-tuning, and embedding search using open-source libraries including LangChain, Hugging Face, and OpenAI APIs. Confidently validate model performance using standard benchmarks and custom metrics.
• Champion strong engineering practices through mentorship and technical guidance, ensuring systems are aligned with data governance and regulatory standards. Collaborate with central teams at Hubspot to enable ML/AI best practices
• Engage in code reviews, testing, and documentation efforts to uphold code quality and maintainability. Mentor junior engineers and data scientists to strengthen their software development skills, optimize algorithms, and stay current with advancements in the field.

About You

• Degree in Computer Science, Statistics, Applied Mathematics, or a related quantitative field.
• Expert knowledge of machine learning and AI techniques, with a strong track record of selecting appropriate methods and successfully deploying multiple models in production, including full lifecycle ownership, development, CI/CD, monitoring, and maintenance
• Strong Python & SQL skills with deep experience in ML/AI libraries such as scikit-learn, TensorFlow, PyTorch, Hugging Face, CrewAI and LangChain.
• Hands-on experience with LLM deployment (workflows & agents), vector search, and RAG pipelines at scale.
• Familiarity with Java is a big plus, especially for internal service integration.
• Knowledgeable in model monitoring, alerting, and evaluation techniques.
• Proficient developing & working with API’s & standard ML deployment stack: Git, Docker, Kubernetes, FastAPI, etc.
• Capable of independently leading ML/AI projects from concept to production.
• Excellent communicator, able to translate complex technical ideas to diverse audiences. Collaborative and creative, thrives in fast-paced, iterative environments.

Bonus Points

• Familiarity with React framework, and RPC functions to expose back-end systems to front-end clients.
• Experience working with Kafka or other stream based processing architecture.
• Familiarity with emerging LLM architectures and techniques in LLM space like Graph RAG, MCP, A2A, Long/Short term memory.

Cash compensation range: 136000-204000 USD Annually