Staff Machine Learning Engineer, Calendly

$157.3-255.2k

Eligible for our Quarterly Corporate Bonus program and equity awards; Salary varies by location

AWS

Docker

Kubernetes

GCP

Python

Tensorflow

Azure

PyTorch

Confluence

Slack

Senior and Expert level

Remote in US

More information about location

Automated appointment scheduling

Be an early applicant

Automated appointment scheduling

501-1000 employees

B2CB2BEnterpriseInternal toolsProductivitySaaSMobileAutomation

Be an early applicant

$157.3-255.2k

Eligible for our Quarterly Corporate Bonus program and equity awards; Salary varies by location

AWS

Docker

Kubernetes

GCP

Python

Tensorflow

Azure

PyTorch

Confluence

Slack

Senior and Expert level

Remote in US

More information about location

501-1000 employees

B2CB2BEnterpriseInternal toolsProductivitySaaSMobileAutomation

Company mission

To provide broad and deep support for various meeting scenarios, and make scheduling easier and more efficient.

Job

Company

Role

Who you are

8+ years of industry experience in applied Machine Learning (or 6+ years with a PhD in a relevant field)
Deep understanding of modern LLMs and Generative AI – Strong familiarity with recent advancements in large language models, their applications, fine-tuning techniques, retrieval-augmented generation (RAG), multimodal models, and agentic frameworks
Strong foundation in machine learning and statistics – Proficiency in probabilistic modeling, statistical inference, hypothesis testing, and traditional ML techniques
Solid software engineering fundamentals – Extensive experience with Python, CI/CD for ML workflows, containerization (Docker, Kubernetes), and monitoring/observability of deployed models
Backend engineering and ML infrastructure – Proven experience in building scalable APIs, integrating ML models into production systems, and deploying on cloud platforms (AWS, GCP, Azure); familiarity with distributed computing and database technologies is a plus
Hands-on with modern ML tooling – Practical experience with PyTorch, TensorFlow, Hugging Face, LangChain, vector databases, and model-serving frameworks
Self-motivated and resourceful – You take initiative, find creative solutions, and don’t let roadblocks stop you from making progress
Bias for action and results-oriented – You thrive in ambiguity, move fast, and focus on delivering impact rather than just building technology; you recognize when to seek assistance and are willing to learn whatever is needed to get the job done
Collaborative & communicative – You can work cross-functionally with engineering, product, analytics and business teams to align on goals and deliver solutions that scale
Curiosity and continuous learning – You stay on top of the latest ML/AI advancements and proactively seek ways to integrate them into real-world applications
You are comfortable working remotely and with enabling tools like Slack, Confluence, etc
Authorized to work lawfully in the United States of America as Calendly does not engage in immigration sponsorship at this time

What the job involves

Well, we are looking for a Staff Machine Learning Engineer who will bring the track record of delivering business value through executing hands-on full machine learning lifecycle
You will report to the head of Data Science & Machine Learning and will be responsible for driving new initiatives using the latest advancements in ML, working closely with cross-functional teams, and helping to drive business insights & growth as well as creating magical experiences for our end customers through innovation
We have a product focus and passion for using machine learning to solve real-world problems, and understand that being an effective MLE is about collaborating with people as much as it is about writing code
You will join a great data team and be an integral part of building new, machine learning-based experiences for internal and external customers alike
Collaborate cross-functionally with software engineers, product managers, and analysts to understand business needs, define priorities, and drive impactful machine learning solutions
Design, develop, and deploy ML models and pipelines at scale, supporting both batch and real-time use cases; architect ML and backend solutions as needed
Leverage cloud-based ML services and tools to build reusable, high-performance systems that enable rapid model development, low-latency inference, and seamless model maintenance
Optimize ML models for scale and efficiency, ensuring they meet latency SLAs while handling Calendly’s production traffic; conduct live experiments to validate and refine model performance

Our take

Calendly is a cloud-based scheduling service that is straightforward to use. It allows around 10 million customers per month to connect and make appointments based on their available times without having to send emails back and forth.

The platform offers four different plans - allowing individuals, small companies, and large enterprises alike to make use of these services. Calendly's growth to date been based mostly around a very organic strategy. Its invites become links to Calendly itself, so people who like it can, and do, start to use it.

There are a handful of competing products on the market, including offerings from Doodle and Microsoft, but Calendly's customer-friendly design has won it attention and allowed it to carve itself a space in the field. Impressive funding has contributed to the company's expansion, allowing it to capitalize on the increasing popularity of home and hybrid working.

Freddie

Company Specialist at Welcome to the Jungle

Insights

Top investors

21% employee growth in 12 months

Glassdoor (3.2)

Trustpilot (3.9)

Company

Funding (2 rounds)

Jan 2021

$350m

SERIES B

Apr 2014

$0.6m

SEED

Total funding: $350.6m

Company benefits

Quarterly Bonus
Equity
Home Office Setup
Technology
Pick Your Own Perk
Flexible Time Off
Vacation Stipend
Parental Leave
Health and Wellbeing
Fun Community Events
401k Company Match

Company HQ

Atlantic Station, Atlanta, GA

Leadership

Tope Awotona

(CEO)

Having studied at the University of Georgia, they worked as an IBM Sales Rep and for Perceptive Software, Vertafore, and EMC as an Account Manager. They left the latter in 2014, having founded Calendly in February 2013.

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