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Lead ML Engineer, Full Stack

Salesforce

Lead ML Engineer, Full Stack

Salesforce

Palo Alto, CA; Seattle, WA

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Remote work flexibility

Learning and development stipend

Top Tier compensation with equity

Health, dental, and vision coverage

Required Skills

Python

Apache Spark

TensorFlow

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.
Job Category
Software Engineering
Job Details

About Salesforce

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword - it's a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.
Ready to level-up your career at the company leading workforce transformation in the agentic era? You're in the right place! Agentforce is the future of AI, and you are the future of Salesforce.

About the role

Salesforce is seeking a passionate and highly skilled AI/SW Engineer to join our team in Tableau developing the #1 AI-powered analytics agents for helping customers see, understand, and act on data.
On the Analytics Agent team, you will work at the forefront of agentic application development, building groundbreaking, multi-modal products and tools that transform how people engage with data.
This is an opportunity to contribute to a dynamic, fast-paced environment, applying your expertise to build scalable, data-intensive systems for analytics. We're looking for curious and motivated engineers who want to play a significant role in pushing the boundaries of what AI agents can achieve.

Key Responsibilities

  • Collaborate with product managers, fellow engineers, and researchers to build next-generation generative AI products and prototypes to make our customers successful.
  • Propose and rapidly iterate on ideas and experiments, as though in a startup environment, to achieve product-market fit for cutting-edge analytics agents.
  • Build and shape user experiences using context engineering and generative AI capabilities.
  • Design and build scalable and performant agentic systems, taking throughput and latency into account, recognizing how and where to apply parallel processing, stream processing, and asynchronous I/O.
  • Evaluate the performance and quality of the agentic solutions you are building against customer use cases.
  • Solve challenges with probabilistic software, ensuring defensive error handling, streaming data optimization, caching, and explainability.
  • Implement logging, tracing mechanisms, and tools to facilitate debugging, diagnostics, and performance tracking.
  • Engage in light DevOps tasks, leveraging infrastructure best practices to deploy and monitor AI-driven systems.

Requirements

  • Adaptable and Innovative Mindset: Fearless about learning new technologies and excited to work in a fast-paced, ambiguous environment. Possess a problem-first approach with a careful and principled methodology for building resilient systems.
  • Expertise in shaping experiences with LLMs and agents.
  • Proficient with evaluation of ML model performance.
  • Strong Programming and Distributed Systems Development Skills: Proficient in Python, Java, or other languages. Experience building full-stack applications with expertise in either backend, frontend, or both. Ability to handle error cases, write asynchronous code, and work effectively with streaming data. Professional experience in developing, scaling, and maintaining applications at a production scale.
  • Experience with Modern Software Development Practices: Familiar with DevOps principles, infrastructure best practices, and cloud-based deployments. Knowledgeable about queues, message buses, and event-driven architectures.

Unleash Your Potential:

When you join Salesforce, you'll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we'll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future - but to redefine what's possible - for yourself, for AI, and the world.
Accommodations
If you require assistance due to a disability applying for open positions please submit a request via this Accommodations Request Form.

Posting Statement:

Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that's inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence

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About Salesforce

Salesforce

A cloud-based software company that provides customer relationship management software and applications.

10,001+

Employees

San Francisco

Headquarters

$243B

Valuation

Reviews

4.0

16 reviews

Work Life Balance

3.0

Compensation

3.5

Culture

2.5

Career

3.0

Management

2.0

35%

Recommend to a Friend

Pros

Competitive compensation packages

Remote work flexibility

Good benefits (headphone/internet reimbursement)

Cons

Ongoing layoffs and job insecurity

Poor refresher/yearly stock grants

Condescending interview processes

Salary Ranges

45 data points

Mid/L4

Senior/L5

Mid/L4 · Analyst Business Intelligence

1 reports

$156,823

total / year

Base

$120,633

Stock

-

Bonus

-

$156,823

$156,823

Interview Experience

5 interviews

Difficulty

3.4

/ 5

Offer Rate

20%

Experience

Positive 20%

Neutral 20%

Negative 60%

Interview Process

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Onsite/Virtual Interviews

5

Final Interview Panel

6

Offer

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Past Experience