Senior Machine Learning Scientist (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
TL;DR
Senior Machine Learning Scientist (AI): Developing and researching machine learning features and algorithms to deliver advanced AI customer service products with an accent on applied ML, product focus, and rapid prototyping. Focus on designing, evaluating, and deploying ML models including supervised, unsupervised, and transformer-based approaches to improve customer experience.
Company
is an AI Customer Service company focused on delivering innovative AI-enhanced support solutions trusted by nearly 30,000 global businesses.
What you will do
- Identify opportunities where ML can add value to customer service products
- Define ML problem framing and research appropriate algorithms
- Collaborate closely with Product, Design, and engineering teams
- Conduct exploratory data analysis and offline evaluation of models
- Develop prototypes and support their production deployment
- Plan, measure, and communicate learnings to inform product iteration
Requirements
- English: B2 level or higher required
- 3-5 years of applied machine learning experience
- Strong knowledge of statistics including experiment design
- Intermediate programming skills
- Advanced education in ML or related field (e.g., MSc)
- Strong communication and scientific thinking skills
Nice to have
- Experience shipping ML products
- PhD or research environment experience
- Expertise in NLP, deep learning, Bayesian methods, reinforcement learning, clustering
- Strong statistics or math background
- Data visualization and SQL skills
Culture & Benefits
- Competitive salary and equity in a fast-growing startup
- Daily lunch, snacks, and stocked kitchen
- Regular compensation reviews and pension scheme
- Comprehensive health and dental insurance for employees and dependents
- Flexible paid time off and parental leave policies
- Cycle-to-Work scheme and equipment support
- Relocation support for those moving to offices
Hiring process
- Technical evaluation of ML skills and experience
- Interviews with cross-functional teams
- Assessment of communication and problem-solving abilities
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