Senior Machine Learning Engineer

Base Poland (Poland); Kraków; On-site; PLN 302,000 - 454,000; Full time

Job summary

Zendesk seeks a Senior ML Engineer to own end-to-end ML-powered features for customer service agents and admins. You will work from prototype to production, building data pipelines, model integration, and ML infrastructure.

You will collaborate with scientists to productionize research, ensuring reliable, scalable ML systems and cost efficiency across the stack. Strong emphasis on mentoring and cross-team collaboration.

Qualifications

• 5+ years in ML-focused software engineering or ML product delivery.
• Strong Python; Ruby experience is a plus.
• Production ML systems with serving, monitoring, and data pipelines.
• Experience with LLMs in production and prompt engineering.

Responsibilities

• Own and deliver ML-powered product features end-to-end: data pipelines, model integration, serving, monitoring, and production iteration.
• Collaborate with scientists to productionize research outputs into reliable, user-facing features.
• Build and maintain ML infrastructure, including model serving, inference pipelines, LLM integrations, and evaluation frameworks.
• Participate in design discussions and architecture decisions across teams.
• Collaborate with product and software engineers to integrate ML capabilities into the product experience.
• Improve reliability, performance, and cost-efficiency of ML systems by addressing issues.
• Mentor junior engineers through code reviews and knowledge sharing.

Skills

ML engineering

MLOps

Python

SQL

Docker

Kubernetes

AWS

LLMs in prod

Tools

Metaflow

MLflow

BentoML

Docker

Kubernetes

Snowflake

dbt

Job description

Job Summary

At Zendesk, the Senior ML Engineer will join the AI Copilot organization, which delivers AI-powered product features directly to customer service agents and administrators. The role involves owning the delivery of ML-powered features at scale, from prototype to production.

Responsibilities

• Own and deliver ML-powered product features end‑to‑end: data pipelines, model integration, serving, monitoring, and production iteration.
• Collaborate with scientists to productionize research outputs into reliable, user‑facing features.
• Build and maintain ML infrastructure, including model serving, inference pipelines, LLM integrations, and evaluation frameworks.
• Participate in technical design discussions and architecture decisions, influencing cross‑team initiatives.
• Collaborate with product and software engineers to ensure ML capabilities are well integrated into the broader product experience.
• Improve reliability, performance, and cost‑efficiency of ML systems by proactively identifying and addressing issues.
• Mentor junior engineers through code review, pairing, and knowledge sharing.

Required Qualifications

• 5+ years of software engineering experience with a focus on ML engineering, MLOps, or building ML‑powered products.
• Fluent in Python; working proficiency in Ruby is a plus.
• Solid experience building and operating ML systems in production (model serving, inference pipelines, monitoring).
• Experience integrating LLMs into production systems (prompt engineering, evaluation, or multi‑provider setups).
• Comfortable with SQL and data infrastructure; able to work with data pipelines, transformations, and data quality.
• Experience with containerised deployments (Docker, Kubernetes) and cloud infrastructure (AWS).
• A track record of owning features end‑to‑end and delivering them to production with high quality.
• Ability to work with uncertainty and pivot as priorities change.
• Strong collaboration skills—effective communication with scientists, product engineers, and product managers.

Preferred Qualifications

• Experience with Snowflake and dbt for data transformations and analytics.
• Hands‑on experience with ML pipeline tooling (e.g., Metaflow) and experiment tracking (e.g., MLflow).
• Experience with model serving frameworks (e.g., BentoML) on Kubernetes.
• Familiarity with ML frameworks such as PyTorch or TensorFlow.
• Experience with event‑driven architectures (e.g., Kafka).
• Experience with iterative, metrics‑driven product development (A/B testing, feature flags, incremental rollouts).

Tech Stack

• Languages: Ruby and Python
• Runtime: AWS
• ML Pipeline: Metaflow
• Experiment Tracking: MLflow
• Model Serving: BentoML on Kubernetes
• Data Storage: S3, RDS MySQL, Snowflake (with dbt)
• Deployment: Kubernetes via Docker
• LLM Proxy: Heavy usage of LLM technology from multiple providers

Salary

The Poland annualized base salary range for this position is zł302,000.00‑zł454,000.00. The actual compensation offered will be based on job‑related capabilities, applicable experience, and other relevant factors. This position may also be eligible for bonus, benefits, or related incentives communicated during the offer stage.

EEO Statement

Zendesk is an equal opportunity employer and we’re proud of our ongoing efforts to foster global diversity, equity, and 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. Zendesk is an AA/EEO/Veterans/Disabled employer.