Senior Machine Learning Engineer

Job Description

Join our team at Zendesk QA (formerly Klaus) to develop cutting-edge customer service quality assurance solutions! We are seeking forward-thinking experts who are keen on building AI-driven tools that reshape the way teams review and analyze their customer interactions.

Our quickly expanding, international team has embraced the innovative mindset from day one. We are looking to complement this team with a Senior ML Engineer who’ll bring expertise working with backend systems, LLM applications and has firm knowledge of ML infrastructure components.

This is a hybrid role based in Estonia.

Our Stack

• Python, Go, Kafka, MySQL, Snowflake
• Kubernetes, AWS, Datadog
• Jenkins, Github Actions & In-house tooling
  
  

What you’ll be doing

• High level of independence and trust - you decide how the implementation is done
• Working independently in a team and delivering high-quality code in a timely manner
• Analysing data to determine the optimal solution, balancing cost, development effort and required functionality
• Building and improving our RESTful and RPC-based APIs to be consumed by various applications (and end-users!)
• Building reusable code and libraries for future use
• Optimizing the application for maximum performance and scalability
• Implementing security and data protection functionalities
• Designing and implementing data storage solutions
• Performing code reviews and providing feedback to your peers
• Set up monitoring systems and continuously monitor application performance to proactively identify and address issues
• Writing automated tests
  
  

What you’ll bring to the role

• At least 3 years of experience with a focus on ML development & data analysis
• Experience with programming languages like Python & Go
• Strong understanding of data and LLM usage
• Working experience with cloud-native technologies like Kubernetes
• Experience with Google Cloud Platform or Amazon Web Services
• Comfortable with working remotely in English across departments
• Excellent written and spoken communication skills
• Interest in machine learning and ML Ops
• Passion to build great customer experiences
  
  

Hybrid: In this role, our hybrid experience is designed at the team level to give you a rich onsite experience packed with connection, collaboration, learning, and celebration - while also giving you flexibility to work remotely for part of the week. This role must attend our local office for part of the week. The specific in-office schedule is to be determined by the hiring manager.

The Intelligent Heart Of Customer Experience

Zendesk software was built to bring a sense of calm to the chaotic world of customer service. Today we power billions of conversations with brands you know and love.

Zendesk believes in offering our people a fulfilling and inclusive experience. Our hybrid way of working, enables us to purposefully come together in person, at one of our many Zendesk offices around the world, to connect, collaborate and learn whilst also giving our people the flexibility to work remotely for part of the week.

Zendesk is an equal opportunity employer, and we’re proud of our ongoing efforts to foster global diversity, equity, & inclusion in the workplace. Individuals seeking employment and employees at Zendesk are considered without regard to race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, ancestry, disability, military or veteran status, or any other characteristic protected by applicable law. We are an AA/EEO/Veterans/Disabled employer. If you are based in the United States and would like more information about your EEO rights under the law, please click here.

Zendesk endeavors to make reasonable accommodations for applicants with disabilities and disabled veterans pursuant to applicable federal and state law. If you are an individual with a disability and require a reasonable accommodation to submit this application, complete any pre-employment testing, or otherwise participate in the employee selection process, please send an e-mail to [email protected] with your specific accommodation request.