Staff Machine Learning Scientist

Reposted 21 Days Ago
Be an Early Applicant
London, England, GBR
In-Office
Senior level
Cloud • Information Technology • Software
Intercom's mission is to make internet business personal - helping businesses connect with their customers.
The Role
As a Staff Machine Learning Scientist, you will focus on hiring and mentoring staff, raising technical standards, and applying machine learning to improve customer experiences. You'll research algorithms, conduct data analysis, and collaborate with teams to produce ML products.
Summary Generated by Built In

Fin, now part of Salesforce, is on a mission to help businesses provide perfect customer experiences.

Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey, from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk, giving modern support teams one single system.

Together with Salesforce, the #1 AI CRM, where humans with agents drive customer success, we're building the future of customer experience. 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.

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.

What's the opportunity? 

Fin's Machine Learning team is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands.

We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated ML product engineers enable us to move to production fast, often shipping to beta in weeks after a successful offline test.

We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy.

What will I be doing? 
  • Play an active role in hiring, mentoring and career development of other engineers
  • Raise the bar for technical standards, performance, reliability, and operational excellence
  • Identify areas where ML can create value for our customers
  • Identify the right ML framing of product problems - Working with teammates and Product and Design stakeholders
  • Conduct exploratory data analysis and research - Deeply understand the problem area
  • Research and identify the right algorithms and tools - Being pragmatic, but innovating right to the cutting-edge when needed
  • Perform offline evaluation to gather evidence an algorithm will work
  • Work with engineers to bring prototypes to production
  • Plan, measure & socialize learnings to inform iteration
  • Partner deeply with the rest of team, and others, to build excellent ML products
What skills might I need? 
  • 5-8 years applied ML experience
  • Previous background in a senior/staff role (data science, software development or academic)
  • Significant, demonstrated impact that your work has had on the product and/or the teams
  • Strong programming skills
  • Experience as the primary technical leader for a team
  • Strong communication skills, both within engineering teams and across disciplines.
  • Comfort with ambiguity
  • Typically have advanced education in ML or related field (e.g. MSc)
  • Scientific thinking skills
Bonus skills & attributes 
  • Track record shipping ML products
  • PhD or other experience in a research environment
  • Deep experience in an applicable ML area - E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering
  • Strong stats or math background
  • Visualization, data skills, SQL, matplotlib, etc.

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.

In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. At Fin, we want to give people what they need to do the best work of their careers. Our benefits and programs are designed to support your health and wellbeing, your family, your time away from work, and your financial future. Offerings vary by location in line with local practices and requirements. Learn more about working at Fin and the benefits we offer at fin.ai/careers. 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. 

Policies 

Fin has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week.

We have a radically open and accepting culture at Fin. We avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone. As an organization, our policy is to not advocate on behalf of the company or our employees on any social or political topics out of our internal or external communications. We respect personal opinion and expression on these topics on personal social platforms on personal time, and do not challenge or confront anyone for their views on non-work related topics. Our goal is to focus on doing incredible work to achieve our goals and unite the company through our core values.  

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 and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.


Skills Required

  • 5-8 years applied ML experience
  • Previous background in a senior/staff role (data science, software development or academic)
  • Strong programming skills
  • Experience as the primary technical leader for a team
  • Typically have advanced education in ML or related field (e.g. MSc)
  • Strong communication skills, both within engineering teams and across disciplines

Intercom Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Intercom and has not been reviewed or approved by Intercom.

  • Healthcare Strength Healthcare is described as comprehensive across regions, with employer‑verified medical, dental, and vision coverage and related protections. Job postings and benefits pages consistently highlight strong core health benefits.
  • Parental & Family Support Parental leave is repeatedly characterized as generous for both birthing and non‑birthing parents, with employer verification on public benefits listings. Family support is emphasized across U.S. and EMEA postings.
  • Equity Value & Accessibility Role postings regularly include equity/RSUs alongside salary, indicating broad access to ownership. Total compensation descriptions consistently feature equity as a meaningful part of the package.

Intercom Insights

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The Company
HQ: San Francisco, CA
900 Employees
Year Founded: 2011

What We Do

Intercom is the next generation customer service platform, built for an AI-first world. Intercom is the only platform that combines an AI Bot + AI Help Desk + Proactive Support tools into one seamless platform. Founded in 2011 and backed by leading venture capitalists, including Kleiner Perkins, Bessemer Venture Partners and Social Capital, Intercom is on a mission to make internet business personal. Our products are great to sell, because they're loved by our customers. We received a “Top Rated” for Live Chat on Trustradius, and we’re a Top 50 product for Small Businesses on G2 - we think these awards speak for themselves.

Why Work With Us

We're a more established company that still feels like a start-up environment. We operate and innovate quickly. Employees have the opportunity to take big bets, make signficiant impact, and advance in their careers.

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