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SurveyMonkey

Staff Machine Learning Engineer

УдалённоItaly только
Опубликовано
Роль
AI / ML
Опыт
Стафф
Занятость
Полная занятость
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Коротко по делу

Staff-level ML engineer with 10+ years in machine learning/data science and production models. Needs strong NLP, LLM product integrations, evaluation platforms, data-at-scale, monitoring, SaaS/AWS experience, and technical leadership. Must be based in Italy and work from a SurveyMonkey office up to 1 day every two weeks.

Ключевые навыки

Machine LearningNatural Language ProcessingLLM

Обязательные навыки

Data ScienceStatistical modellingHuman-In-The-Loop labellingExploratory data analysisLLM-as-JudgeAWSKafkaEKSSageMakerAthenaCI/CDAgentsRAGPrompt engineering

Чем предстоит заниматься

  • Serve as a technical leader for ML/AI product initiatives.
  • Author, approve, and guide architectural decisions.
  • Establish standards and frameworks that can be adopted across ML initiatives.
  • Handle deliverables, delegate effectively, and mentor engineers across teams.
  • Architect scalable ML platforms and production data pipelines.
  • Collaborate cross-functionally to integrate new data sources.
  • Build and own end-to-end ML/AI solutions within the product.
  • Maintain long-term ownership of ML/AI solutions through deployment, refinement, and iterative enhancements.
  • Create novel and traditional ML/AI implementations for the in-product experience.
  • Collaborate with Product, Design, Front-End, and Back-End developers to educate teams and iterate through solutions and designs.
  • Build end-to-end monitoring and telemetry systems to detect complex failure modes, deterioration of predictive accuracy, and usage patterns.
  • Deliver tailored AI solutions by training, fine-tuning, and deploying models ranging from statistical methods to cutting-edge LLMs.
  • Build productive partnerships across all stakeholder levels, from non-technical stakeholders to domain experts.
  • Drive continuous improvement and innovation through research.
  • Propose adoption strategies for external solutions.
  • Identify knowledge gaps within the team.
  • Ensure hiring and training initiatives address capability needs.

Что требуется

  • 10+ years of experience in Machine Learning and Data Science, building and maintaining models in production environments.
  • Strong expertise in Natural Language Processing, statistical modelling and analysis, and modern ML methods.
  • Deep understanding of models and what is happening within them.
  • Hands-on experience building novel architectures for bespoke product solutions.
  • Experience handling data at scale with familiarity in Human-In-The-Loop labelling, training and scaling usable data, plus foundational exploratory data analysis.
  • Proven expertise in creating evaluations and evaluation platforms for non-deterministic systems, including LLM-as-Judge techniques, inferred signals, and traditional model evaluation mechanisms to validate performance and maximise ML/AI impact.
  • Experience developing production monitoring and creating feedback loops using active feedback, passive signals, and user behaviours to identify key performance indicators for user journeys and experiences.
  • SaaS development and deployment experience, building multi-scaled, right-sized ML solutions in SaaS environments.
  • Experience with CI/CD code lifecycle practices in AWS environments and services including Kafka, EKS, SageMaker, and Athena.
  • Demonstrated experience building LLM-powered product integrations, including Agents and autonomous processes, RAG and context enrichment, and modern prompt engineering methods with guided generation and oversight.
  • Proven leadership and mentorship capabilities as a technical leader with the ability to mentor engineers across teams and manage complex deliverables.
  • Required to work from a SurveyMonkey office for up to 1 day every two weeks.

Преимущества

  • Flexible, hybrid environment.
  • Thoughtfully designed offices.
  • CHOICE Fund to help employees thrive in work and life.
  • People from all backgrounds can make an impact, build meaningful connections, and grow their careers.
  • Company values such as championing inclusion and making it happen are embedded into hiring, collaboration, and growth.
  • Accommodations are available for applicants with disabilities.

Global online survey, forms and feedback SaaS platform used by businesses, researchers (and students) and individuals

SaaSКрупнаяsurveymonkey.com/
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