Software Engineering MTS/SMTS

Company: Salesforce
Location: San Francisco
Posted on: January 27, 2025

Job Description:

Software Engineering MTS/SMTS
Apply remote type Office Tech-Flexible locations Washington - Bellevue California - San Francisco time type Full time posted on Posted 2 Days Ago job requisition id JR280073
To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.
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.
Job Description
At Salesforce, we are reimagining how organizations build and deploy advanced AI and machine learning products! Our Einstein platform is at the forefront of democratizing Generative AI, Predictive AI, and AI Agents, enabling businesses to rapidly create, deploy, and manage intelligent applications.
By seamlessly integrating large language models (LLMs), AI Agents, and Predictive AI across all Salesforce clouds, we empower customers to transform their workflows, applications, and customer experiences with innovative, AI-driven capabilities.
What You Will Do:

• 
  
• Design & Lead High-Scale Machine Learning Services: Work with pioneering technologies like Sagemaker, TensorFlow, PyTorch, Triton, and Spark to build scalable, distributed machine learning services on a modern containerized stack using Kubernetes and Spinnaker.
  
• Drive Microservices Architecture: Lead the design, development, and ongoing optimization of microservices architectures for machine learning pipelines, APIs, and model management systems.
  
• Ownership of Core Technology: Take ownership of core platform technologies related to orchestrated machine learning APIs, from design to delivery, driving continuous improvement and scalability of the platform.
  
• Lead High-Impact Engineering Initiatives: Take the lead on projects that significantly impact product growth, applying your expertise to mentor engineers and make strategic technical decisions.
  
• Maintain Service Reliability: Balance live-site management with the delivery of new features and technical debt resolution. Participate in on-call rotations to resolve complex, real-time issues and ensure high availability of services.
  
• Build and Scale Data Services: Work with AWS, GCP, and other cloud providers to build and scale Big Data and real-time data applications.
  
  Core Responsibilities:
  
  • 
    
  • Contribute to the long-term technical roadmap and strategy for the Einstein Platform team.
    
  • Own technical initiatives that push the boundaries of machine learning and AI at Salesforce, influencing key design decisions and product features.
    
  • Lead by example in technical execution, mentoring and coaching team members to tackle complex challenges and grow in their roles.
    
  • Drive end-to-end ownership of critical AI features, from the architecture and design phase through to deployment, maintenance, and scaling.
    
    Core Qualifications:
    
    • 
      
    • 3+ years of hands-on experience with Big Data, machine learning, and microservices architectures.
      
    • Proven experience leading highly impactful projects, from inception to delivery, with a focus on large-scale machine learning services (e.g., training & inference pipelines, predictive and generative models).
      
    • Strong programming expertise in JVM-based languages (Java, Scala) and Python.
      
    • Experience with distributed systems and cloud platforms like AWS, GCP, or Azure, including services like OpenSearch, DynamoDB, EMR, S3, and Google Cloud ML.
      
    • Expertise with open-source projects and technologies such as Spark, Kafka, Feast, and Iceberg.
      
    • Solid understanding of containerization (e.g., Docker, Kubernetes) and cloud-native deployment patterns.
      
      Preferred Qualifications:
      
      • 
        
      • Deep experience with machine learning platforms like Amazon SageMaker or Google Cloud AI.
        
        Accommodations
        If you require assistance due to a disability applying for open positions please submit a request via this Accommodations Request Form.
        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.
        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 welcomes all.
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Keywords: Salesforce, San Jose , Software Engineering MTS/SMTS, IT / Software / Systems , San Francisco, California