[BA-206] Associate Data Engineer / Data Engineer - Machine Learning

[BA-206] Associate Data Engineer / Data Engineer - Machine Learning

02 May

02 May



Job Details

The Customer Success and Growth (CSG) organization at Salesforce is responsible for onboarding, customer support, professional services, training, partner certification, and developing long-term relationships with Salesforce customers. The Customer Intelligence (CI) group in CSG creates data driven intelligence on customers’ usage and engagement, which in turn is used to help customers leverage the world’s best CRM platform, through cutting edge data products and deep data science & modeling. The Data Engineering team within the Customer Intelligence group is the backbone of data for the group, which creates, maintains and automates the data for data science modeling and predictive apps.


We are looking for an ML engineer who can ignite the vision of ML Engineering in this team. As a key member of this group you will have immense opportunities to work on a broad range of problems and technologies, designing ML pipelines for the data science models ass well as operationalizing them. You will be working with a group of world-class data scientists, product managers and business analysts to build intelligent services for both internal teams and customer-facing products. We share a passion for problem solving, new technologies, and learning, so you will be highly encouraged to explore new technologies and come up with innovative solutions that could take our data science automation capabilities to the next level 


- Experience working with relational databases (Oracle, Postgres and/or distributed computing platforms, and their query interfaces - SQL, Map Reduce, PIG, Hive etc)

- Experience in end to end processing - ingestion, transformation, model scoring and operationalisation of scalable data science solutions

- Good understanding of data science/machine learning fundamentals, algorithms & complexity involved

- Strong knowledge of Object Oriented design, advanced algorithms, data structures, design patterns, etc.

- Experience building and maintaining ML pipelines/ frameworks in production 

- Strong passion to automation and creation of highly efficient and error free operational models/ pipelines

- Experience in PaaS environments like Heroku/GCP/AWS will be a big plus

- Experience with Automation tools like Airflow is plus


- Bachelor’s or Master’s degree in Computer Science/ Software Engineering and/or with relevant work experience 

- At least 2 years solid hands-on experience in distributed, scalable systems (Spark, Hive, Pig, Map Reduce) 

- 3+ years experience in writing complicated database queries in SQL (Oracle, Postgres, Hive, etc)

- Advanced proficiency in at least one scripting language: Python, Java, Scala or similar

- At least 2+ years of experience working with machine learning libraries such as sklearn, XGBoost, TensorFlow, PyTorch, etc

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