Lead Software Engineer

Salesforce is a leading customer relationship management (CRM) platform that believes in improving the state of the world through business.
$176,800 - $265,200
Machine Learning
Staff Software Engineer
Hybrid
5,000+ Employees
4+ years of experience
AI · Enterprise SaaS

Description For Lead Software Engineer

Salesforce, a leading customer relationship management (CRM) platform, is seeking a Lead Software Engineer to join their team in San Francisco, CA. This role offers an exciting opportunity to work at the forefront of machine learning and data science, creating impactful products for one of the world's most innovative companies.

As a Lead Software Engineer, you'll be part of a dedicated team of machine learning professionals, tackling a wide range of challenging problems. Your work will involve forecasting significant business metrics, developing churn and propensity models, and applying clustering and classification techniques to both structured and unstructured data. You'll play a crucial role in creating high-visibility data products and decision-making tools that will be used by Salesforce's leadership team.

This position requires a strong technical background, with a Bachelor's degree in Computer Science, Engineering, or a related quantitative field, along with at least four years of relevant experience. You should be proficient in Python and SQL, with expertise in machine learning frameworks such as PyTorch and TensorFlow. A deep understanding of machine learning concepts, optimization theory, probability theory, statistics, and linear algebra is essential for success in this role.

Your responsibilities will include leading efforts to enhance core products, refining and developing new data science products and workflows, and building tools to monitor data pipeline performance and model production. You'll also be instrumental in establishing best practices for coding standards, workflows, and product automation, as well as scaling the operations of the data science team through automation and library development.

Salesforce offers a competitive salary range of $176,800 to $265,200 per annum for this position, along with a comprehensive benefits package. The company is committed to creating an inclusive and diverse workplace, providing equal opportunities for all qualified applicants.

This role offers a hybrid work arrangement, with the option for telecommuting and some travel to Salesforce offices as required. It's an excellent opportunity for a skilled engineer looking to make a significant impact in the field of machine learning and data science while working for a company that values innovation and social responsibility.

Join Salesforce and be part of a team that's not just building cutting-edge technology, but also striving to improve the state of the world through ethical business practices and a commitment to equality.

Last updated an hour ago

Responsibilities For Lead Software Engineer

  • Work closely with a dedicated team of machine learning professionals on various problems including forecasting, churn modeling, and classification
  • Create high-visibility data products and decision-making tools for Salesforce's leaders
  • Lead efforts to improve core products in terms of engineering maturity and architecture
  • Refine and develop new data science products, workflows, tools, and automation
  • Build tools to monitor data pipeline performance, data quality, and models in production
  • Establish best practices with coding standards, workflows, tools, and product automation
  • Review and maintain existing tool-set and codebase
  • Scale the operations of the data science team by building automation and libraries

Requirements For Lead Software Engineer

Python
  • Bachelor's degree in Computer Science, Engineering, or a related quantitative discipline
  • 4 years of progressively responsible experience in the job offered or related field
  • Proficiency in Python
  • Experience with SQL
  • Knowledge of PyTorch and TensorFlow
  • Expertise in Deep Learning and Machine Learning
  • Familiarity with Numpy and Pandas
  • Understanding of Optimization Theory
  • Knowledge of Probability Theory and Statistics
  • Proficiency in Linear Algebra

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