Machine Learning Engineer - AI Research
Location
Palo Alto, CA | United States
Job description
Description
Machine Learning Engineer | AI Research
Note: By applying to the Machine Learning Engineer| AI Research posting, recruiters and hiring managers across the organization hiring machine learning engineers will review your resume. Our goal is for you to apply once and have your resume reviewed by multiple hiring teams.
Salesforce is looking for an exceptional Machine Learning Engineer| AI Resercher to help us take on one of the world’s most extensive data sets and transform it into amazing products that feel like magic. You will work on innovative AI applications and products. Brainstorming data product ideas with data scientists and engineers to build data products used by hundreds of millions people every day.
In your role as a Machine Learning Engineer | AI Research, you will partner with analysts, engineers, designers, executives, product managers, marketers, customer success, and sales team members across all Cloud businesses to create ML-driven decision making data products that enable our partners to affect the bottom line and solve critical business problems.
Your Impact: - Work closely with a dedicated team of machine learning professionals on a wide range of problems including forecasting significant business metrics such as sales and capacity, churn and propensity modeling to retain and grow our customer base, clustering and classification using both structured and unstructured data, and more!
- Help create high-visibility data products and decision-making tools for Salesforce’s leaders
- Lead the charge on taking our core products to the next level 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 (pipelines, models, algorithms); continue to improve existing tools and build new ones
- Scale the operations of the data science team by building automation and libraries
Required Skills:
- A related technical degree required
- 4+ years of industry experience and a passion for crafting, analyzing and deploying machine learning-based solutions
- Experience working as part of a team with mature data science products
- Consistent record in building software and data products using modern development lifecycle methodologies: CI/CD, QA, and Agile Methodologies
- Applied experience designing, building and optimizing data pipelines, architectures and data sets
- Experience deploying, monitoring and maintaining data science products in cloud environments such as AWS or Microsoft Azure
- Good understanding of Machine Learning methods and Statistics, including ML project lifecycle and associated challenges at each stage of development
- Proficient at writing good quality, well-documented and tested, scalable code - Python preferred. Experience with tools like mlFlow, Airflow, Docker and Cloud Platforms such as AWS/GCP is ideal
- Solid understanding of data transformations and analytics functions using tools/languages like Pandas, Sklearn, SQL and Spark
- Strong communication skills and ability to interface well with other engineers, data scientists and product managers
- Passion, curiosity, solutions focus and independence
For roles in San Francisco and Los Angeles: Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.
Job tags
Salary
