Machine Learning Engineer

Wishlist’s mission is to amplify company performance by igniting the power of people. We understand that companies don’t build a business, they build people, and the people build the business. Our rewards and recognition platform takes human psychology, digitizes it, and then connects people to business performance.

We accomplish our mission through our values:
Build the House
Be Memorable
Win Together
Seek Solutions

We are looking for a talented and experienced machine learning engineer to build efficient, data-driven artificial intelligence systems that advance our predictive automation capabilities. The candidate should be highly skilled in statistics and programming, with the ability to confidently assess, analyze, and organize large amounts of data as well as a deep understanding of data science and software engineering principles.

*Responsibilities - *

• Design, develop, and optimize recommendation systems, leveraging content-based, collaborative, and hybrid filtering techniques.
• Conduct end-to-end development of recommendation algorithms, from prototyping and experimentation to deployment and monitoring.
• Build and maintain data pipelines to support real-time and batch recommendation use cases.
• Implement KNN search, cosine similarity, semantic search, and other relevant techniques to improve recommendation accuracy.
• Utilize A/B testing and other experimental methods to validate the performance of recommendation models.
• Collaborate with cross-functional teams, including product managers, engineers, and designers, to define recommendation requirements and ensure effective integration.
• Monitor, troubleshoot, and improve recommendation models to ensure optimal system performance and scalability.
• Document models, experiments, and analysis results clearly and comprehensively.
• Stay up-to-date with the latest ML/AI and Gen AI trends, techniques, and tools, bringing innovative ideas to enhance our platform and improve the customer experience.

*Required Skills - *

• 3+ years of experience in building recommendation systems, with a strong understanding of content-based, collaborative filtering, and hybrid approaches.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field.
• Strong knowledge of machine learning techniques, statistics, and algorithms related to recommendations.
• Proficiency in Python, R, or similar programming languages.
• Hands-on experience with ML libraries and frameworks (e.g., TensorFlow, PyTorch, Scikit-Learn).
• Experience with KNN search, cosine similarity, semantic search, and other similarity measures.
• Familiarity with NLP techniques and libraries (e.g., spaCy, Hugging Face) to improve content-based recommendations.
• Hands-on experience deploying recommendation systems on cloud platforms like AWS, GCP, or Azure.
• Experience with MLflow or similar tools for model tracking and lifecycle management.
• Excellent problem-solving abilities and experience in data-driven experimentation and A/B testing.
• Strong communication skills and ability to work effectively in a collaborative team environment.

*Benefits - *

• Competitive salary as per the market standard.
• Directly work with the Executive Leadership.
• Join a great workplace & culture.
• Company-paid medical insurance for you and your family.