Senior Machine Learning Engineer [GROWTH]

1 нед. назад

PolandEuropeSeniorOnsite

machine learningpythondata engineering

Senior Machine Learning Engineer role in Warsaw at working on scalable, data-driven products for personalized user interactions.

Обязанности

The Communications tribe, a key part of the Growth Alliance, enables our brands to deliver highly personalized, meaningful interactions with our users across global markets. As a Senior Machine Learning Engineer within this team, you will drive a direct business impact by shaping the intelligence behind how, when, and what we communicate with our customers.
Your work will primarily focus on three core initiatives:
Send Decisioning: Improving the data layer and integration for the decisioning engine, specifically utilizing the company's existing feature store and feature sets, to optimize our communication channels (email, SMS, and push notifications). Your models will automate the logic that determines the most relevant message and timing for each individual user.
Intelligent Funnel: Supporting a collaborative, cross-tribe initiative aimed at personalizing the post-click experience. You will streamline the content generation process to reduce manual work when creating email marketing copy.
AI-Assisted Content & Search: Developing automated asset retrieval to select images based on context during email creation, moving away from manual selection. Additionally, you will develop tools that assist marketing teams in the automated composition of new, high-performing communication assets.
To succeed in this project, you should be a pragmatic and curious problem solver who excels in a cross-functional environment. Success involves translating complex user behavior into scalable models, identifying opportunities to improve our data foundations, and balancing technical depth with a strong focus on driving user engagement.
At HelloTech, flexibility and cross-functional collaboration are core to how we work. While this role is aligned to a specific Alliance, strong candidates may also be considered for opportunities across different teams or projects.

Условия

Global collaboration at scale: Collaborate with experienced engineers and product partners across HelloTech’s international teams, in a culture of active knowledge sharing.
Technology with real-world impact: Build and operate modern systems at global scale, supporting 6+ millions of customers and complex supply chain operations.
Technical/Product/Design leadership: Drive best practices and influence architecture/design, quality, and ways of working in an autonomous, product-led setup.
End-to-end development/delivery: Drive decisions from problem definition to production, improving systems and enabling long-term scalability.
Access to workspace at Warsaw centre (Prosta 20). The hub offers modern facilities including showers, breakout zones, outdoor space, cycle parking, and refreshments (coffee, soft drinks, and fruit).
Are you the missing ingredient? If this sounds like a tasty opportunity, we’d be excited to hear from you.  We aim to review your profile and respond within 5 business days. #MACHINELEARNING

Другое

Work with in Warsaw and its HelloTech organisation, ’s global technology backbone with more than 1000 people, building the digital products that power our end-to-end food experience. From meal kits and ready-to-eat meals to specialty offerings like pet food and premium meat & seafood, HelloTech creates the platforms that bring tailored food solutions to millions of customers every month.
Our subscription-based, direct-to-consumer model relies on technology at every step, from customer-facing apps and personalization logic to pricing, forecasting, supply chain optimization, and initiatives that help reduce food waste. While our brands operate independently to serve distinct customer needs, they are united by shared platforms, data, and operational excellence built by HelloTech.
HelloTech works in autonomous, cross-functional alliances, each owning a specific product or domain end to end. By working with our Warsaw office, you will help shape scalable, data-driven products used across our markets, working with a modern tech stack and international teams to continuously improve how people discover, order, and enjoy ’s products, today and in the future.
Own & elevate ML infrastructure: Build, maintain, and refine the core repositories, developer tooling, and engineering workflows that enable the team to organize, scale, and deploy production ML systems smoothly.
Architect the Send Decisioning data layer: Evaluate, optimize, and potentially redesign our communication platform integrations - building robust pipelines and integrating our feature store to enhance data quality and feature availability for decisioning models.
Engineer AI-assisted content & asset systems: Develop scalable integrations and workflows to streamline email copy generation (subject lines, copy context) and build context-driven asset retrieval systems for marketing teams.
Build production-grade pipelines & serving layers: Translate research and experimentation into low-latency, highly reliable production systems, ensuring continuous observability, data reliability, and error handling.
Bridge research & production: Partner closely with Data Scientists to transition experimental models into resilient, low-latency production services with high observability and robust fallback mechanisms.
Set the ML engineering standard: Build, standardize, and maintain core repositories, CI/CD templates, and ML platform practices (Databricks, MLflow) to streamline how the team develops and deploys code.
Operate & scale ML infrastructure: Take full accountability for production reliability—monitoring input data quality, drift, and latency across critical communication and personalization funnels.
(Ideally) 5+ years of experience building and operating production ML systems.
Fluency across the data and ML stack (Python, Spark, Databricks) and working knowledge of the backend and platform stack (Go, Kafka, Kubernetes), with hands-on experience across pipelines, model serving, and observability at scale.
Statistical literacy to design honest experiments and the judgment to evaluate model metrics accurately.
Operational judgment to diagnose system misbehavior under real load, identify root causes, and deploy robust fixes.
Hands-on experience with AI tooling (Claude Code, Cursor, Copilot) as part of a regular technical workflow, with a practical sense of how context engineering shapes output quality.
Product sense: an analytical viewpoint on what should be built and why, with the ability to translate technical initiatives into business value.
A bias to ship , maintaining full accountability to finish the final implementation phases of a project.
Above all, we are looking for individuals who will make better. We believe there are many different ways of developing skills and we love diverse experiences! So even if you don’t “tick all the boxes” but think you’d thrive in this role, we would really like to learn more about you.