Machine Learning Engineer - Multiple Positions
Salary not listed • Italy - Remote • Full-time
Posted 1mo ago
Job Location
Italy - Remote
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
Machine Learning Engineer
About the job
SurveyMonkey is seeking talented Machine Learning Engineers to join their organization, which spans both the Machine Learning Platform (MLP) team and the Product Data Science team. You will work at the intersection of Data Science, DevOps, and Product, contributing to enterprise-scale NLP and ML systems. The roles involve building and owning end-to-end ML/AI solutions, architecting scalable platforms and data pipelines, and delivering tailored AI solutions by training, fine-tuning, and deploying models. This is an opportunity to drive continuous improvement and innovation, with roles available for engineers at various career stages, from early career to Staff Engineer.
Responsibilities
- Build and own end-to-end ML/AI solutions within the product, managing deployment, refinement, and iterative enhancements.
- Develop end-to-end monitoring and telemetry systems to detect failure modes, accuracy deterioration, and usage patterns.
- Architect scalable ML platforms and production data pipelines, integrating new data sources.
- Create novel and traditional ML/AI implementations for the in-product experience, collaborating with cross-functional teams.
- Deliver AI solutions by training, fine-tuning, and deploying models, including statistical methods and LLMs.
- Drive continuous improvement and innovation through research and proposing adoption strategies for external solutions.
Requirements
- Extensive professional experience in Machine Learning and Data Science, with a focus on building and maintaining production models.
- Strong expertise in Natural Language Processing, statistical modelling, and modern ML methods, with hands-on experience building novel architectures.
- Experience handling large datasets, including Human-In-The-Loop labelling and exploratory data analysis.
- Proven expertise in creating evaluations and evaluation platforms for non-deterministic systems, including LLM-as-Judge techniques.
- Experience developing production monitoring and feedback loops using active feedback, passive signals, and user behaviours.
- SaaS development and deployment experience, building scalable ML solutions in SaaS environments with CI/CD practices on AWS (Kafka, EKS, SageMaker, Athena).
- Demonstrated experience building LLM-powered product integrations, including Agents, RAG, and prompt engineering methods.
- Proven leadership and mentorship capabilities as a technical leader.