Data Scientist

1 day ago


Bengaluru, India Sureminds Solutions Full time

Description : Machine Learning Engineer Recommender Systems | 4-8 Years | Bangalore (Hybrid) | ContractWere looking for passionate and skilled Machine Learning Engineers experienced in Recommendation Systems to join our clients dynamic teamIf you love building intelligent personalization systems, working on large-scale data, and solving real-world ML challenges this role is for youPosition DetailsLocation : Bangalore (Hybrid)Experience : 4-8 YearsBill Rate : As per market standardsHiring Type : Contract.Client Interview : YesRole Overview :As a Machine Learning Engineer (Recommender Systems), youll design, build, and optimize models that drive personalized experiences for millions of users.Youll work with cutting-edge tools, data pipelines, and neural architectures to power real-time recommendations and product ranking engines. Key Responsibilities :- Build end-to-end recommendation systems collaborative filtering, content-based, and neural recommenders (Two-Tower / Dual Encoder).- Develop and optimize embedding-based retrieval and similarity search.- Design scalable ML pipelines using Python, TensorFlow, PyTorch, Scikit-learn.- Work with large-scale distributed data systems (Spark, BigQuery).- Define and track evaluation metrics (Recall@K, NDCG, MAP).- Apply Computer Vision (image embeddings) & NLP (product text embeddings).- Build real-time search & personalization engines.- Hands-on with Predictive & ML models deployment.- Use cloud platforms (AWS / GCP / Azure).- Collaborate across teams to drive AI-powered innovation in fashion retail & e-commerce.Required Skills :- Bachelors / Masters / PhD in Computer Science, Data Science, or Machine Learning.- Strong background in Recommendation Systems Collaborative Filtering, Neural Networks, Embedding Models.- Proficiency in Python, SQL & ML frameworks (TensorFlow, PyTorch, Scikit-learn).- Experience with Spark, BigQuery, and distributed computing.- Cloud knowledge : AWS / GCP / Azure.- Exposure to CV + NLP, real-time personalization, and predictive modeling.- Domain : Fashion Retail / E-commerce personalization (preferred).Nice to Have :- Familiarity with Vector Databases (FAISS, Milvus, etc.)- Exposure to MLOps & CI/CD automation- Published research or open-source ML project contributionsWhy Join Us :- Work on high-impact ML systems influencing millions of users- Exposure to latest AI/ML stacks & large-scale data- Collaborative & innovative environment- Opportunity to deploy your models in real business use cases (ref:hirist.tech)


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