Job Description

This role is for one of the Weekday's clients

Salary range: Rs 2500000 - Rs 3000000 (ie INR 25-30 LPA)

Min Experience: 5 years

Location: Ahmedabad

JobType: full-time

We are seeking a skilled Machine Learning Engineer to build and optimize intelligent systems that power personalized user experiences. This role focuses on developing recommendation engines, retrieval systems, and data-driven AI solutions that enable users to discover relevant content, connections, and insights seamlessly. Sitting at the intersection of machine learning, data engineering, and applied AI, you will design scalable systems that leverage real-time data, embeddings, and advanced algorithms. The ideal candidate is passionate about solving complex problems, building production-grade ML systems, and translating data into meaningful, high-impact user experiences.

Requirements

Key Responsibilities

• Design, build, and deploy recommendation systems for personalized user experiences
• Develop ranking and scoring algorithms to improve relevance, engagement, and discovery
• Implement and optimize Retrieval-Augmented Generation (RAG) pipelines for AI-driven applications
• Build and manage embedding-based retrieval systems using vector databases
• Process and analyze user behavior data to improve personalization and model performance
• Design and maintain data pipelines for training, inference, and real-time processing
• Collaborate with cross-functional teams to integrate machine learning models into production systems
• Continuously monitor, evaluate, and improve model performance in terms of accuracy, latency, and scalability
• Work with APIs and backend systems to deploy and maintain ML solutions
• Stay updated with advancements in machine learning, AI, and retrieval systems to enhance system capabilities

What Makes You a Great Fit

• Strong foundation in machine learning, algorithms, and statistical modeling
• Proficiency in Python and relevant ML libraries (NumPy, Pandas, Scikit-learn, etc.)
• Hands-on experience building recommendation systems or ranking models
• Practical knowledge of RAG systems, embeddings, and similarity search techniques
• Experience working with vector databases such as Pinecone, Weaviate, or FAISS
• Familiarity with deploying ML models in production environments and working with APIs
• Strong problem-solving skills with the ability to work on real-world datasets and user behavior data
• Understanding of deep learning frameworks and modern AI techniques is a plus
• Experience with scalable systems, real-time processing, or distributed architectures is advantageous
• Ability to collaborate effectively in cross-functional teams within fast-paced environments
• Strong ownership mindset with a focus on building impactful, user-centric solutions