Lead/Senior Machine Learning Engineer - Commerce Cloud Einstein

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

About Futureforce University Recruiting

Our Futureforce University Recruiting program is dedicated to attracting, retaining and cultivating talent. Our interns and new graduates work on real projects that affect how our business runs, giving them the opportunity to make a tangible impact on the future of our company. With offices all over the world, our recruits have the chance to collaborate and connect with fellow employees on a global scale. We offer job shadowing, mentorship programs, talent development courses, and much more.

Job Category

Products and Technology

Job Details

Salesforce Commerce Cloud is the global leader of Cloud-based (SaaS) E-Commerce solutions that enable the world’s premier retailers to maintain a robust online shopping presence. We empower our clients to improve their ROI by giving them the tools to effortlessly design and deploy seamless E-Commerce sites across the web, mobile, tablet, and in-store applications. Commerce Cloud provides a highly scalable, integrated cloud platform that allows our clients to rapidly launch and manage multiple e-commerce stores, initiate unique marketing campaigns, and drive customer traffic across a global footprint. Our model serves for an environment of constant innovation that extends to our technology and internal company culture. Come join our platform serving 3000+ sites with more than one billion unique visitors.

We are looking for a top-notch Data Scientist to join the Commerce Cloud Einstein data science team. Our team is tasked with producing machine learning models to enhance and personalize the shopper experience with semantic search, product recommendations, content personalization, and much more. In addition, we augment and automate the work of the merchandiser to enable them to react faster and better to changing markets, trends, and customer demands. You will be responsible for turning business needs into production machine learning systems. You will do research explorations, machine learning systems design, prototyping and building, large-scale training and tuning, and production system experiments.

The successful candidate will work with world-class database gurus, software/ML engineers, research scientists, and fellow data scientists. We are looking for someone who gets a kick out of staying on top of the latest machine learning and data science literature, tools, and techniques and figuring out the best way to apply these for practical solutions. We encourage contribution to tools and knowledge within the team, across the company, and outside the company.

Responsibilities

• Work with product management and leadership to translate business problems to data science problems
• Research, prototype and build demonstrations of machine learning ideas for quick validation and feedback
• Design and build machine learning systems to hit accuracy and performance metric targets
• Productize machine learning systems in collaboration with engineering teams
• Design and conduct experiments to ensure optimal performance of machine learning systems
• Educate engineering and product teams about data science during collaboration
• Mentor and collaborate with other members of the data science team
• Share technical innovations to the team and across the company
• Create new innovations and contribute to conferences and/or open-source tools

Qualifications

Must-Have

• Fluent in prototyping/building machine learning models and algorithms and wrangling large datasets
• MS or Ph.D. in a quantitative discipline with 2+ years of relevant experience or a BS in a quantitative discipline with 5+ years of relevant experience
• Knowledgeable about classical as well as deep learning machine learning approaches (Regression, Cross-Validation, Boosting, Matrix-Factorization, Decision Trees, Clustering, reinforcement learning, CNNs, RNNs, contrastive learning, GANs, Transformers, deep reinforcement learning)
• Proficient in using Python scientific stack (Numpy, Pandas, PyTorch, SciPy, Jupyter, ...) to implement machine learning models and algorithms
• Proficient in shell scripting, Unix/Linux command-line tools, working with cloud infrastructure (ideally AWS)
• Great communication skills and ability to discuss with scientists, engineers, designers, and product managers

Ideally

• Ph.D. with 5-10 years of relevant experience
• Experience in shipping machine learning model systems into large scale production systems
• Experience in building machine learning models for (e-commerce) search

Accommodations

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