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About Salesforce

We’re Salesforce, the Customer Company, inspiring the future of business with AI+ Data +CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too — driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good – you’ve come to the right place.

Do you want to be at the forefront of a team at Salesforce that is making history? Do you want to build technology and new science that millions of people will use? Are you excited about working on large scale Generative AI, Natural Language Processing (NLP), and Deep Learning? Salesforce is in the best position in the industry to turn AI hype into real products and revenue.

The Sales Cloud data apps team at Salesforce is looking for senior data scientists with hands on experience modeling different use cases, to help us take one of the world's most extensive data sets and transform it into magical product experiences.

We are looking for strong and recognized experts in NLP and generative AI, to help design and develop intelligent, personalized and trusted CRM generative and predictive AI applications. You will play a critical role in incorporating artificial intelligence, generative, and predictive AI into Salesforce products. You will participate in the end-to-end AI product development lifecycle. You will design and develop the scalable deep learning and generative AI system and services, and partner with AI Platform Engineers, Software Engineers to define requirements, design and develop reusable workflow and ML pipeline.

Key Responsibilities:

• Design and deliver scalable generative AI services that can be integrated with many applications, thousands of tenants, and run at scale in production.
• Develop machine learning software and models that can generalize across hundreds of thousands of Salesforce customers, but can automatically adapt to each of their individual features.
• Drive system efficiencies through automation, including capacity planning, configuration management, performance tuning, monitoring and root cause analysis.
• Collaborate with data scientists across Salesforce and built some of the most exciting data products that hundreds of millions people use every day.
• Work with fellow engineers, communicating and collaborating effectively to build the infrastructure and take the prototype models to production.
• Meeting with external customers and understanding their businesses and their challenges.
• Wrangle large data sets and work with internal product teams to transform and sprinkle machine learning fairy dust on various products.

What we care about:

• You are a domain expert - You have deep industry experience and fluency in wrangling large datasets, prototyping/building machine learning models and algorithms, and, shipping models/ML pipeline into large-scale production systems. Preferably 5-10 years of industry experience [PhD. for Principal/Architect level]
• You have to love data - this is what we do. We are looking for people who are excited about different and unique data sets, and all the ways that they could be used in order to improve user experience.
• You love to make a difference - we don't like status quo. We are looking for people who want to excel at everything they do, while still being able to prioritize between the must-haves and nice-to-haves.
• You are a very quick learner - we face new challenges every day, anything that ranges between the operating model of a financial services companies to how to make Spark work with the S3 file system. No school could prepare you for all of these, so you need to be very quick on your feet.
• You are self driven - we operate like a startup, so everyone needs to do a bit of everything. You don't need to be an expert, but you need to not shy away from tasks outside of your comfort zone.

Requirements:

Must-have:

• Designing/managing/evaluating data labeling tasks, plus use of industry standard tool(eg Prodigy)
• Firsthand experience with different AI techniques/models for enterprise applications, including: intent classification, clustering/nearest neighbour analysis, summarisation, question answering, etc.
• Experience with processing of raw data for model training, testing and validation
• Experience implementing systems to process millions of users and/or billions of data points in a production environment.
• Experience working with modern ML library and frameworks: Tensorflow/Keras, JAX+Flax, Pytorch, Transformers, etc
• Experience with distributed, scalable systems and modern data storage, messaging and processing frameworks, including Kafka, Spark, Docker, Hadoop, etc.
• Driving model accuracy requirements with project stakeholders.Identifying and adopting suitable model architectures, often in ambiguous or unclear scenarios.

Nice-to-have:

• Experience with LLMs,retrieval augmented generation (RAG), soft prefix/prompt tuning, fine tuning
• Experience with techniques/tools in explainable AI
• Experience with multilingual, multimodal AI

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