Machine Learning Engineer

| SaaS | Real Estate |

Job Title: Machine Learning Engineer

Job-Type: Full-Time

Competitive Salary: $110,000 - $135,000 per year with Quarterly bonus and stock options

About Us:

At Romvu, we are the Content Factory for real estate agents, fully automating content production, publishing, advertising, and customer acquisition. Our innovative platform leverages AI to identify trending topics, create realtor-branded videos, and optimize social media ad campaigns—all designed to empower agents like never before. With over 250,000 customers across cities like Vancouver, Toronto, Los Angeles, San Francisco, Miami, and New York, our technology integrates seamlessly with major real estate boards, ensuring our content is both geographically relevant and credible.

Job Description:

We are looking for an experienced Machine Learning Engineer to help build and optimize advanced Human-in-the-Loop (HITL) AI models for reading, summarizing, and analyzing news content. The successful candidate will have a strong foundation in natural language processing (NLP), text summarization, and contextual analysis, combined with practical experience in designing machine learning systems that can iteratively improve through human feedback.

As a key member of our team, you will be responsible for developing AI-driven models that not only summarize news articles but also extract deeper context, sentiment, and key insights. You will collaborate closely with data scientists, product managers, and engineers to deploy these models into real-world applications.

Key Responsibilities:

• Develop and Optimize AI Models: Build, train, and fine-tune machine learning models that process large volumes of news data, summarize articles, and extract key insights.
• Text Summarization & NLP: Design and implement NLP algorithms for both extractive and abstractive summarization, ensuring summaries are coherent, concise, and contextually relevant.
• Context Analysis & Sentiment Extraction: Develop models that can understand and analyze the context and sentiment behind news articles, including tone, intent, and underlying themes.
• Human-in-the-Loop System Design: Integrate human feedback mechanisms to continuously improve AI model performance, addressing challenges like biases, accuracy, and alignment with user preferences.
• Model Evaluation & Iteration: Continuously assess and improve model accuracy and reliability through A/B testing, user feedback, and data analysis.
• Collaboration: Work with cross-functional teams including product managers and other engineers to ensure models align with business objectives and technical requirements.
• Data Collection & Annotation: Assist in sourcing and curating high-quality training datasets, including news articles, to ensure the AI models are trained with diverse and accurate information.

Skills & Qualifications:

• Machine Learning & AI Knowledge: Strong understanding of machine learning algorithms, with hands-on experience in applying them to natural language processing and text analysis tasks (e.g., classification, clustering, summarization).
• Natural Language Processing (NLP): Expertise in key NLP techniques such as abstractive and extractive summarization, named entity recognition (NER), topic modeling, sentiment analysis, and semantic parsing.
• Human-in-the-Loop Systems: Experience in designing systems where human input is integrated to refine and improve model outputs iteratively.
• Programming Languages: Proficiency in Python and relevant machine learning libraries like TensorFlow, PyTorch, spaCy, Hugging Face Transformers, scikit-learn, or NLTK.
• Deep Learning Frameworks: Familiarity with deep learning techniques and frameworks, particularly for NLP tasks (e.g., RNNs, LSTMs, Transformers).
• Data Processing & Feature Engineering: Experience with data wrangling, text preprocessing, and feature extraction techniques for unstructured text data.
• Contextual & Sentiment Analysis: Ability to design models that understand subtle nuances in language such as sarcasm, irony, and other complex sentiments within the news.
• Evaluation Metrics & Model Fine-Tuning: Familiarity with performance metrics such as precision, recall, F1 score, and BLEU for evaluating NLP models.
• Version Control & Collaboration Tools: Experience with version control systems (e.g., Git) and collaboration platforms (e.g., Jira, Confluence) for agile development.
• Problem-Solving & Critical Thinking: Strong analytical skills with the ability to troubleshoot model issues, debug code, and suggest improvements based on testing and evaluation results.

Preferred Qualifications:

• Master's degree or PhD in Computer Science, Data Science, Machine Learning, or a related field.
• Experience with large-scale real-time data processing and deployment of machine learning models into production environments.
• Familiarity with cloud platforms like AWS, GCP, or Azure for deploying and scaling machine learning models.
• Knowledge of ethics in AI and bias mitigation strategies for NLP systems.

Key Language and Skills:

• Programming: Proficiency in Python, experience with libraries such as TensorFlow, PyTorch, spaCy, and Hugging Face.
• NLP Expertise: In-depth knowledge of abstractive and extractive summarization, named entity recognition, sentiment analysis, and contextual understanding.
• Machine Learning Algorithms: Expertise in classification, clustering, and deep learning models tailored to NLP.
• Human-in-the-Loop (HITL): Experience integrating human feedback into the AI model development cycle.
• Model Evaluation: Strong understanding of performance metrics for NLP models, such as F1 score, BLEU, and other text-based evaluation metrics.
• Collaboration Tools: Familiarity with Git, Jira, and cloud-based platforms for version control and project management.
• This revised version focuses more on the Machine Learning Engineer role, emphasizing the technical expertise required, without including the Chief of Staff role. It provides a comprehensive look at the candidate's skills in NLP, HITL systems, and practical AI deployment.

Why Join Us?

• Work at the cutting edge of AI technology and contribute to real-world applications in the media and news sectors.
• Be part of a fast-paced, collaborative team focused on solving complex, high-impact challenges.
• Opportunity for personal and professional growth as you work on challenging projects in the rapidly evolving field of AI.

What We Offer:

• Competitive Salary and performance-based bonus
• PTO and paid holidays
• Health & Wellness: Dental Care, Private Practitioner, and Extra Health benefits
• Flexible Work Environment: Hybrid/remote options available, depending on role and company policy.
• Professional Development: Elevate your Skills with opportunities for growth and professional advancement
• Team Spirit: Join our weekly 'happy hour' and engage in fun team-building events
• Small Company, Big Heart: Experience the warmth of a tight-knit work environment in a small company.

Roomvu is proud to be an Equal Opportunity Employer. We evaluate qualified applicants without regard to Ethnicity, national origin, religion, sex, sexual orientation, gender identity, disability,protected veteran status, and other statuses protected by law.

Roomvu has appeared on Inman News, TechCrunch, Forbes, Drastic Summit, Yahoo News, and more. We're backed by the National Association of Realtors's Second Century Ventures and work with industry leaders in real estate to facilitate their growth.