ML Engineer (Natural Language Processing) at Unsweetened Beauty

Responsibilities:

AI-Powered Reviews:

Develop algorithms to scrape the web for product reviews.

Analyze sentiment around products using natural language processing (NLP) techniques.

Categorize reviews based on product attributes.

Create AI-powered ingredients scoring models.

Use product ingredients to generate recommendations for similar products.

Highlight safe/unsafe ingredients personalized to each user.

Implement product image matching algorithms for scoring.

Hyperpersonalization Based on User Attributes:

Utilize user attributes such as age, gender, location, hormones, skin type, skin concerns, lifestyle, and preferences for personalization.

Recommend personalized product quantities based on user behavior and preferences.

Cluster products based on user relevance and preferences.

Implement personalized and semantic search algorithms.

Develop real-time relevancy ranking of search results.

Search Enhancement:

Build autocomplete predictive search to anticipate user intent.

Implement an out-of-stock search feature that suggests semantically similar items.

Create advanced filtering options for search results.

Recommendation Systems:

Develop cross-selling and upselling strategies across product categories.

Suggest products based on user profiles, items added to the cart, user interests, site interactions, and similar user behavior.

Provide personalized "Frequently Bought Together" and "You Might Also Like" product recommendations.

Categories for You:

Suggest relevant products from the entire brand's product range or marketplace based on user preferences and behavior.

Personalized Menus:

Customize user menus to enhance their experience and facilitate easy access to relevant features and products.

Trending for You:

Personalize trending product recommendations based on user preferences and interactions.

Requirements:

Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field.

2-3 years of experience in AI/ML engineering.

Proficiency in Python and relevant machine learning libraries (e.g., TensorFlow, PyTorch).

Strong understanding of NLP and sentiment analysis.

Experience with recommendation systems, personalization, and search optimization.

Knowledge of web scraping techniques and data preprocessing.

Excellent problem-solving and communication skills.

Ability to work collaboratively in a fast-paced environment.