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Intern
MuleSoft, a Salesforce company, is defining the application network category and changing the $700Bn IT integration market. This rapid growth drives the urgent need to scale our data and analytics organization quickly and efficiently and take friction out of our processes, platforms, and systems. Our team’s mission is to empower business users to unlock the endless capabilities of data, build new opportunities for innovation, and turn insights into competitive advantage.
The MuleSoft AI & ML team sits within the MuleSoft Data Organization and is a new and growing team. We collaborate with product owners to bring innovation to the customers by using data and AI power.
We're looking for talent to add to our team who have good programming skills and a background in one or more of the following domains: Machine Learning, Deep Learning, Recommendation, Natural Language Processing (NLP), Time-series Forecasting, and data mining.
** Responsibilities:**
Partner with product owners, data architects, domain experts, data analysts and other teams to translate business requirements into critical metrics and models.
Contribute to the research, design and construction of ground breaking ai-powered features that improve our users experience.
Rapidly iterate and develop machine learning models for the features under development.
Implement cleaning, transforming, and loading the data and extracting features to store in feature storage.
Support the ML lifecycle management infrastructure (AWS Sagemaker).
Participate in architecture and code reviews.
Identify, document and promote best practices.
Constantly learn, have a clear pulse on innovation across machine learning, data science and AI fairness.
Engage with business stakeholders to understand requirements of features and map them to the appropriate ML models
Answer open ended questions by extracting interesting and actionable insights from data
Qualifications:
Must-Have :
Enrolled and working towards BS or MS in Computer Science, Data Science, Machine Learning or related field. Please note that in order to be eligible for an internship, we require that you be returning to school the following quarter/semester to work towards completing your degree
Must be attending a College/University in the U.S.
Deep knowledge in one or more of machine learning / deep learning / personalization / NLP / Language Models / ranking.
Experience in building/prototyping machine learning models and algorithms and wrangling large datasets
Proficient in using Python (e.g., numpy, scikit-learn, tensorflow, pytorch, keras, huggingface) to implement machine learning models and algorithms
Proficient in shell scripting, SQL and Unix/Linux command-line tools
Ability to summarize and clearly convey technical topics to multiple audiences
Driven by the opportunity to build products, with a get-it-done approach and a strong bias towards action.
Intellectual curiosity, creative problem-solving and time management skills
Proven track record of delivering outstanding high impact projects in multifaceted settings
Embodies Salesforce and MuleSoft values, particularly ownership, make it awesome, customer-centric, and trust
Ideally:
Experience with big data & emerging technologies (Cassandra/Spark/Flink/Vowpal )
Hands-on experience with other AWS services (Redshift, S3, Lambda, EC2, etc).
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For California-based roles, the base salary hiring range for this position is $50 to $65.
For Washington-based roles, the base salary hiring range for this position is $50 to $65.
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