Software Engineer MTS/SMTS- ML Engineer
India - Bengaluru
Applications have closed
Salesforce
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Job Category
Software EngineeringJob Details
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.
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.
Einstein products & platform democratizes AI and transforms the way our Salesforce Ohana builds trusted machine learning and AI products - in days instead of months. It augments the Salesforce Platform with the ability to easily create, deploy, and manage Generative AI and
Predictive AI applications across all clouds. We achieve this vision by providing unified, configuration-driven, and fully orchestrated machine learning APIs, customer-facing declarative interfaces and various microservices for the entire machine learning lifecycle including Data, Training, Predictions/scoring, Orchestration, Model Management, Model Storage, Experimentation etc.
We are already producing over a billion predictions per day, Training 1000s of models per day along with 10s of different Large Language models, serving thousands of customers. We are enabling customers' usage of leading large language models (LLMs), both internally and externally developed, so they can leverage it in their Salesforce use cases. Along with the power of Data Cloud, this platform provides customers an unparalleled advantage for quickly integrating AI in their applications and processes.
What you’ll do:
Design and deliver scalable generative AI services that can be integrated with many applications, thousands of tenants, and run at scale in production.
Drive system efficiencies through automation, including capacity planning, configuration management, performance tuning, monitoring and root cause analysis.
Participate in periodic on-call rotations and be available for critical issues.
Partner with Product Managers, Application Architects, Data Scientists, and Deep Learning Researchers to understand customer requirements, design prototypes, and bring innovative technologies to production
Participate in meal conversations with your team members about really important topics, such as: Should the cuteness of panda bears be a factor in their survivability? Is love a decision tree or a regression model? How far ahead would society be today if we had 12 fingers instead of 10?
Required Skills:
2+ years of industry experience of ML engineering in building AI system and/or services.
Working with Sagemaker, Tensorflow, Pytorch, Triton, Spark, or equivalent large-scale
distributed Machine Learning technologies on a modern containerized deployment stack
using Kubernetes, Spinnaker, and other technologiesExperience building Distributed microservices on AWS, GCP or other public cloud
substratesExperience with LLMs and prompt engineering
Strong experience building and applying machine learning models for business applications
Proven ability to implement, operate, and deliver results via innovation at large scale
Experience with distributed, scalable systems and modern data storage, messaging and processing frameworks, including Kafka, Spark, Docker, Hadoop, etc.
Good working knowledge of Deep Learning and Machine Learning algorithms.
Grit, drive and a strong feeling of ownership coupled with collaboration and leadership.
Preferred Skills:
Experience in developing deep learning models with complex business use cases and big amount of unstructured data.
Solid Machine Learning Engineering background and familiarity with state-of-the-art deep learning techniques especially for NLP.
Expertise with applying LLMs, prompt design, and fine-tuning methods
Strong background in ML approaches and techniques, ranging from Artificial Neural Networks to Bayesian methods
Experience with conversational AI
Fantastic problem solver; ability to solve problems that the world has not solved before
Excellent written and spoken communication skills
Demonstrated track record of cultivating strong working relationships and driving collaboration across multiple technical and business teams
Accommodations
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Posting Statement
At Salesforce we believe that the business of business is to improve the state of our world. Each of us has a responsibility to drive Equality in our communities and workplaces. We are committed to creating a workforce that reflects society through inclusive programs and initiatives such as equal pay, employee resource groups, inclusive benefits, and more. Learn more about Equality at www.equality.com and explore our company benefits at www.salesforcebenefits.com.
Salesforce is an Equal Employment Opportunity and Affirmative Action Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, or disability status. Salesforce does not accept unsolicited headhunter and agency resumes. Salesforce will not pay any third-party agency or company that does not have a signed agreement with Salesforce.
Salesforce welcomes all.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: APIs AWS Bayesian Conversational AI Deep Learning Docker Engineering GCP Generative AI Hadoop Kafka Kubernetes LLMs Machine Learning Microservices ML models NLP Prompt engineering PyTorch SageMaker Salesforce Spark TensorFlow Unstructured data
Perks/benefits: Career development
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