About the team & opportunity
What’s so great about working on Calendly’s Engineering team?
We make things possible for our customers through impactful innovation.
At Calendly, a Senior Machine Learning Engineer will be able to help drive new initiatives and push the boundaries on what is possible by using the latest advancements in ML. You have a product focus and passion for using machine learning to solve real-world problems, and understand that being an effective engineer 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.
On a typical day, you will:
- Work with unique, large structured time series data sets to build and continuously improve innovative machine learning models for Calendly product use cases
- Work collaboratively with partners including software engineering, product managers, decision and data scientists, to impact the business by understanding and prioritizing requirements for machine learning models
- Hands-on develop, "productionize," and operate machine learning models and pipelines at scale, including both batch and real-time use cases
- Leverage machine learning cloud services and tools to develop reusable, highly differentiating and high-performing machine learning systems, enable fast model development, low-latency serving and ease of model quality upkeep
- Optimize ML models to meet latency SLAs at the scale of Calendly's production traffic and launch live experiments to evaluate model performance
What do we need from you?
- 5+ years of industry experience in applied Machine Learning, inclusive MS or PhD in relevant fields
- Strong programming (Python / Scala / Java / etc) and data engineering skills
- Proficiency in ML frameworks such as: Keras, Tensorflow and PyTorch (in that order of importance) and ETL and ML workflow frameworks like Apache Spark, Beam, Airflow, VertexAI
- Working knowledge of semantic search and embeddings
- Familiarity with Retrieval-Augmented Generation techniques to improve content quality
- Familiarity with orchestration frameworks such as LangChain or Microsoft Semantic Kernel
- Deep understanding of Machine Learning processes (e.g. training/serving skew minimization, feature engineering, feature/model selection), algorithms (e.g. personalization and recommendation, anomaly detection, natural language processing)
- Consistent record of efficiently implementing ML models using a managed service (VertexAI / Sagemaker) for high traffic, low latency, large data applications that produced substantial impact on the end users
- Ability to recognize when to seek assistance and willing to learn whatever is needed to get the job done; ideally, you have some research experience
- Strong verbal and written communication skills; 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’s in it for you?
Ready to make a serious impact? Millions of people already rely on Calendly’s products, and we’re still in the midst of our growth curve — it’s a phenomenal time to join us. Everything you’ll work on here will accelerate your career to the next level. If you want to learn, grow, and do the best work of your life alongside the best people you’ve ever worked with, then we hope you’ll consider allowing Calendly to be a part of your professional career.
Our Hiring Process:
Typically, individuals will participate in the following interview process. However, there may be slight nuances given the role and or department we are hiring for. Please keep in mind that individuals can be declined from the position at any stage of the process.
- Qualified individuals will be invited to schedule a phone interview with a member of our recruiting team. This is a great time to ask any initial questions you have about the company or the role.
- Next, we’ll put you in direct contact with your potential manager. You’ll get a chance to learn even more about life at Calendly, the responsibilities within your role, and the qualities needed to succeed here.
- Then, you will perform an interview exercise, where you can highlight your skills.
- Next, or in parallel, you’ll meet with your potential team members.
- Finally, we connect with those you’ve worked with before, to learn more about the impact you can make, the value you bring, and the best way to set you up for success at Calendly.
We aim to provide an inclusive and equitable experience to everyone who expresses interest in working at Calendly. The recruiter assigned to this role will keep you informed every step of the way. Have questions? Let your recruiter know! Want to share your experience? We are passionately committed to improving and building on our process, and we consider feedback a gift.
If you are an individual with a disability and would like to request a reasonable accommodation as part of the application or recruiting process, please contact us at email@example.com .
Calendly is registered as an employer in many, but not all, states. If you are located in Hawaii, you will not be eligible for employment.
Candidates residing in California may visit our Notice at Collection for California Candidates here: Notice at Collection
Compensation is based on a variety of factors including but not limited to location, experience, and job-related skills. In addition, Calendly offers a wide range of best in class total rewards . This includes comprehensive employee benefits like healthcare, dental, vision, parental leave, 401(k) match, paid time off, and much more. At Calendly we believe exceptional performance deserves exceptional rewards! During the hiring process, we are committed to sharing details about the compensation range for the position, enabling you to make an informed decision.
Please note that the compensation details listed in role postings reflect the base salary only, and do not include bonus/commission, equity, or benefits.