The digital workspace for visual collaboration
MURAL is a leading digital workspace for visual collaboration, founded in 2011 and headquartered in Chinatown, San Francisco, CA. The platform serves a diverse customer base, including IBM, Autodesk, and SAP, and has raised $216.8 million in funding, achieving a valuation exceeding $2 billion. MURAL...
MURAL offers company equity, comprehensive health insurance, fertility benefits, and a unique MURALvida stipend. Employees enjoy a fully remote work e...
MURAL fosters a unique culture centered around visual collaboration and remote work flexibility. The platform encourages creativity and innovation, al...
Mural • Argentina Remote
The Data Engineering team at Mural builds scalable, high-performance systems that transform complex data into actionable insights. We power internal analytics and user-facing features, supporting critical products powered by AI/Machine Learning like Customer Insights, Personalization, Reporting APIs, and Audit Logs. Our work integrates diverse data sources, optimizes core data models, and ensures seamless access across the organization. Success is measured not only by system reliability and scalability but also by the business impact we deliver enabling users to make informed decisions and driving overall customer success.
You will drive product innovation by leveraging advanced AI/ML techniques. You’ll design, develop, and optimize models for classification, recommendation and predictive insights, translating complex business problems into scalable AI solutions that enhance the product experience and drive innovation.
Design, implement, and deploy AI/ML models for classification, regression, recommendation, and predictive analytics.
Apply AI/ML techniques such as RAGs, vector search and embedding where relevant.
Translate business problem statements into end-to-end ML solutions.
Collaborate with Data Engineering to ensure clean, well structured data pipelines for model training and evaluation.
Work with Product and Engineering teams to integrate ML models into production systems and product features.
Analyze and visualize model outputs and customer behavior to drive product decisions.
Prototype, iterate, maintain models while ensuring high quality, reliability, and maintainability.
Contribute to improving team best practices, review code, and mentor peers in ML engineering techniques.
Use AI tools as a part of your fundamental workflows.
4+ years of experience designing, building, and deploying large scale ML systems in production.
Proven ability to translate business problems into end-to-end ML solutions.
Deep expertise in supervised and unsupervised learning, reinforcement learning, and deep learning techniques.
Experience with large language models such as GPT, BERT, OpenAI, and embedding/vector search.
Proficiency in Python (NumPy, Pandas, scikit-learn) and SQL.
Experience with cloud-based ML platforms (AWS, Azure, GCP, Databricks) and big data frameworks (Hadoop, Spark).
A passion for utilizing AI-driven solutions to solve complex problems and enhance user experiences.
Experience learning new technologies, platforms, stacks, and coming up to speed quickly on large codebases
Strong problem-solving skills, collaboration, and emotional intelligence, with experience delivering value in a rapid-growth or startup environment.
Familiarity with data governance and ethical AI considerations
Experience with MLOps and Data Engineering practices
Experience with TensorFlow, PyTorch systems for advanced AI/ML applications.
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
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