Senior Machine Learning Engineer, AI Agent

HubSpot Overview:

HubSpot is an all-in-one marketing, sales, and service software platform that helps businesses grow and succeed. With a user-friendly interface and powerful tools, HubSpot enables businesses to attract, engage, and delight customers, ultimately driving growth and increasing revenue. From marketing automation to CRM, HubSpot offers a comprehensive solution that empowers businesses to succeed in the digital age.

Job Summary:

As a Sr Machine Learning Engineer on the AI Agent team, you will play a critical role in helping build cutting-edge, composable solutions that leverage Large Language Models (LLMs). Our mission is to create a low-code composable UI that empowers product teams and, ultimately, our customers to rapidly develop scalable, reliable, and high-quality AI agents that deliver exceptional user experiences.

You will collaborate closely with a diverse team of Back-End Engineers, Front-End Engineers, and other ML Engineers to integrate the latest advances in LLM and NLP technologies. Your work will contribute directly to building a platform that simplifies the development of intelligent, adaptable agents, optimizing both usability and performance. Together, we aim to push the boundaries of AI-driven automation, offering seamless, intuitive tools that make building sophisticated AI solutions accessible to a wide range of users.

Responsibilities:

• Design and develop machine learning models and tooling for pre-training and/or fine-tuning open source large language models. 
• Experience with the modern LLM stack incl. Retrieval augmented generation, parameter efficient fine-tuning, LoRA, etc. 
• Implement and fine-tune models using state-of-the-art libraries such as Hugging Face Transformers, PyTorch, TensorFlow, and LangChain.
• Research, experiment with, and integrate new LLM technologies such as OpenAI’s GPT models, Meta’s LLaMA, Mistral, Anthropic’s Claude, and Falcon.
• Collaborate with product managers to define and refine requirements and use cases for conversation intelligence.
• Analyze and preprocess data from a variety of sources including numeric, text and other mediums
• Conduct experiments and evaluations of machine learning models, using statistical methods and visualization tools to assess performance and identify areas for improvement
• Keep up to date with the latest research and trends in Generative AI, and contribute to the development of new algorithms and techniques
• Participate in code reviews, testing, and documentation activities, ensuring high quality and maintainability of the codebase
• Experience or interest in mentoring other team members and proactively sharing knowledge

Requirements:

• A degree in Computer Science, Engineering, or related fields, with a focus on machine learning, natural language processing, or speech analysis
• 5+ years of experience in developing and deploying machine learning models and algorithms, preferably in speech or text analysis domains
• Proficiency in Python programming with experience using Hugging Face Transformers or other NLP libraries.
• Hands-on expertise with LLM architectures such as GPT, GPT-Neo, BERT, LLaMA, or Falcon.
• Familiarity with a variety of feature engineering techniques for both text and numeric data would be great
• Experience mentoring other team members and helping to define best practices for the group
• Excellent communication and collaboration skills, with the ability to work effectively in a fast-paced, interdisciplinary team environment.

If you are passionate about leveraging machine learning to transform the way businesses interact with their customers in a collaborative work environment, come join us in HubSpot AI Group!

Cash compensation range: 165500-248300 USD Annually

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The cash compensation above 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 based on a few different factors unique to each candidate, including their skills, experience, qualifications and other job-related reasons.

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