Full-Time
Lead Member of Technical Staff
AI Research
Updated on 9/12/2026
Salesforce
10,001+ employees
Cloud-based CRM platform with subscriptions
Compensation Overview
$172.5k - $285.8k/yr
Company Historically Provides H1B Sponsorship
Palo Alto, CA, USA
Hybrid
Tech-flexible office schedule; required on-site frequency is not specified.
 AI & Machine Learning (1) |
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- Exceptional engineering skills.
- Deep machine learning knowledge with meaningful implementation experience.
- Strong proficiency in Python and solid experience with C++ and/or Java.
- Strong software engineering fundamentals in data structures, algorithms, and system design.
- Practical experience with large language models and agentic workflows, including tool use, planning, memory, and multi-step reasoning.
- Experience building end-to-end artificial intelligence agents or complex AI-driven applications.
- Familiarity with prompting, orchestration, and evaluation for large-language-model-based systems.
- Hands-on experience with deep learning frameworks.
- Strong understanding of machine learning fundamentals.
- Experience implementing and debugging model training, evaluation, and inference pipelines.
- Experience deploying machine learning systems using Docker and cloud platforms such as Amazon Web Services, Google Cloud Platform, or Microsoft Azure.
- Familiarity with distributed training or inference and performance optimization.
- Experience using artificial intelligence tools such as Claude Code, GitHub Copilot, Codex, or Cursor in development workflows.
- Advanced prompt engineering skills and the ability to write precise, structured prompts and cultivate reliable, secure, production-ready system context.
- Work closely with software engineers, product managers, and solution engineers to design, implement, and iterate agentic artificial intelligence systems with customers.
- Create new solutions and define new product categories at the frontier of artificial intelligence.
- Build and ship high-quality, production-grade software using modern engineering practices and artificial intelligence development tools.
- Design and orchestrate complex systems in which artificial intelligence agents integrate with human workflows.
- Contribute to building and maintaining the shared system context repository of system designs, constraints, and standards.
- Evaluate human- and artificial-intelligence-generated code for correctness, quality, security, and performance.
- Build production-quality systems.
- Build and maintain model training, evaluation, and inference pipelines.
- Deploy machine learning systems and optimize distributed training or inference performance.
- Competitive coding experience, including ACM International Collegiate Programming Contest participation or equivalent.
- Experience as a startup founder in agentic artificial intelligence or large language model systems, such as a Y Combinator-backed startup.
- A deep and strategic approach to technical problem-solving.
- Experience building exceptional product experiences in fast-paced environments.
Salesforce provides cloud-based CRM software to help organizations manage customer relationships. Its main platform, Customer 360, combines marketing, sales, service, commerce, and IT tools in one integrated suite delivered via subscription. It differentiates itself with a broad, modular product lineup, a large ecosystem of partners and training, and cloud-based updates. Its goal is to help businesses of all sizes improve customer relationships, streamline operations, and drive growth by delivering consistent, data-driven experiences across the customer journey.
Company Size
10,001+
Company Stage
IPO
Headquarters
San Francisco, California
Founded
1999
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Simplify's Take
What believers are saying
- Agentforce ARR topped $1.5 billion in Q2 2026, up over 240% year over year.
- Second-quarter 2026 revenue reached $11.3 billion, with current RPO rising 14% to $33.5 billion.
- Salesforce led HiBob’s September 1, 2026 investment, extending its HR and Slack ecosystem reach.
What critics are saying
- February 2026 and June 2026 layoffs show AI productivity is shrinking headcount fast.
- Claude token costs cut FY2026 operating margin guidance to 20.1%, pressuring profits.
- Microsoft and AI-native copilots threaten CRM user interfaces, risking Salesforce becoming only plumbing.
What makes Salesforce unique
- Salesforce’s April 2026 AgentExchange unifies AppExchange, Slack, and Agentforce.
- Customer 360 still anchors sales, service, commerce, and IT workflows across enterprises.
- Salesforce’s June 2026 Data 360 semantic search binds customer context to agents.
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Benefits
Health Insurance
Life Insurance
401(k) Retirement Plan
Remote Work Options
Flexible Work Hours
Parental Leave
Wellness Program
Growth & Insights and Company News
6 month growth
↑ 0%1 year growth
↑ 0%2 year growth
↑ 0%Cantor Fitzgerald raised its price target on Salesforce to $300 from $250, maintaining an Overweight rating. Analyst Matthew VanVliet believes the company's open-platform strategy positions it as an early enterprise AI winner. The firm argues that AI won't displace Salesforce but will allow the company to remain the underlying enterprise platform even as customers use other models. This approach could counter fears about AI disrupting software-as-a-service businesses. However, Salesforce's recent growth isn't entirely organic. Informatica contributed approximately $456 million to second-quarter revenue, adding four percentage points to reported growth. As of the second quarter, 99 hedge funds held positions in Salesforce. The company's Agentforce ARR exceeded $1.5 billion, up more than 240% year-over-year.
Salesforce shares rose 2.75% to $264 on Thursday following Snowflake's strong quarterly results. The cloud-data company reported 37% growth in product revenue, with artificial intelligence driving roughly half of the acceleration. Salesforce's second-quarter revenue increased 11% to $11.3 billion. Current remaining performance obligations climbed 14% to $33.5 billion. The company's Agentforce and Data 360 products generated nearly $3.9 billion in annual recurring revenue, including more than $1.5 billion from Agentforce. At $264, Salesforce trades 22% below its estimated fair value of $339. The combined AI and data run rate represents approximately 8.6% of annualised quarterly revenue. Snowflake's performance suggests enterprise AI spending is materialising, though Salesforce must demonstrate it can capture similar budgets.
Salesforce attributed its flat profit margin guidance to heavy spending on Anthropic's Claude AI model. Deputy CFO Mike Spencer told the Deutsche Bank Technology Conference that the company's operating margin is projected at 20.1% for the full year, down from 20.5% in Q2, due to Claude token costs. Spencer said Salesforce deployed Claude in its research and development cycle six months ago to accelerate product development. However, the company is now entering "refinement mode", selecting specific models for particular tasks rather than using the most advanced models for everything. The CRM giant is optimising costs across multiple AI providers, including OpenAI, Cursor, Claude, and testing X's Grok. CEO Marc Benioff previously disclosed expectations to spend $300 million with Anthropic in 2026.
Jim Cramer attributes the recent rebounds of Palantir and Salesforce to a combination of strong earnings and the collapse of a major hedge fund betting against enterprise software. According to Seeking Alpha data, Palantir surged 51% in August whilst Salesforce climbed nearly 40%. Both companies delivered strong quarterly results. Palantir posted 93% Q2 sales growth and raised its full-year outlook, whilst Salesforce beat expectations and expanded its Anthropic partnership. However, Cramer argues the turnaround also stems from the implosion of Situational Awareness, a leveraged hedge fund that controlled $45 billion and bet against enterprise software. "Once that hedge fund blew up, the whole group came roaring back," Cramer said on Mad Money.
Funding will accelerate product development and global deployment of the Wonderful AI OS, as enterprises move from isolated AI use cases to organization-wide transformation.