Staff Machine Learning Engineer

What's the opportunity?

Intercom'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-focused 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?

Identify areas where ML can create value for our customers

Contribute to finding the right ML framing of a product problem

Work with teammates and Product and Design stakeholders

Take algorithms which work offline, and put them in a production setting

Deeply understand and modify as needed

Solve hard scalability and optimization problems

Run production ML infrastructure, evolve it over time

Build new data infrastructure to enable exploration

Establish processes for large scale data analyses, model development, validation, and implementation

Work with teammates to measure and iterate on algorithm performance

Partner deeply with the rest of the team, and others, to build excellent ML products

What skills might I need?

These are meant to be indicative, not hard requirements.

Excellent pragmatic engineering skills

Familiarity with tools used to write, test, deploy, debug, and monitor software

Comfort owning features from inception to outcome

7+ years experience in a production environment, with contributions to the design and architecture of distributed systems

We're looking for engineers who can confidently put ML-powered features in production

Strong communication skills, both within engineering teams and across disciplines

Excellent programming skills

Comfort with ambiguity

BSc in Computer Science, or similar knowledge

Bonus skills & attributes

Deep knowledge of AWS services

ML Ops experience

Large scale computation experience

Track record shipping ML products

Experience in a research environment

Algorithmic optimization experience

Advanced education in CS, ML, Math, Stats, or similar

Practical stats knowledge (experiment design, dealing with confounding, etc.)

Experience in an applicable ML area (e.g., NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering)

Visualization, data skills, SQL, matplotlib, etc.

Benefits

We are a well-treated bunch, with awesome benefits! If there's something important to you that's not on this list, talk to us!

Competitive salary and equity in a fast-growing start-up

We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen

Regular compensation reviews - we reward great work!

Pension scheme & match up to 4%

Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents

Flexible paid time off policy

Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones

If you're cycling, we've got you covered on the Cycle-to-Work Scheme, with secure bike storage too

MacBooks are our standard, but we're happy to get you whatever equipment helps you get your job done

Relocation support for those moving to our offices

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