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3.0 - 5.0 years

8 - 10 Lacs

Hyderabad, Bengaluru, Delhi / NCR

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Strong in Python and experience with Jupyter notebooks, Python packages like polars, pandas, numpy, scikit-learn, matplotlib, etc. Must have: Experience with machine learning lifecycle, including data preparation, training, evaluation, and deployment Must have: Hands-on experience with GCP services for ML & data science Must have: Experience with Vector Search and Hybrid Search techniques Must have: Experience with embeddings generation using models like BERT, Sentence Transformers, or custom models Must have: Experience in embedding indexing and retrieval (e.g., Elastic, FAISS, ScaNN, Annoy) Must have: Experience with LLMs and use cases like RAG (Retrieval-Augmented Generation) Must have: Understanding of semantic vs lexical search paradigms Must have: Experience with Learning to Rank (LTR) techniques and libraries (e.g., XGBoost, LightGBM with LTR support) Should be proficient in SQL and BigQuery for analytics and feature generation Should have experience with Dataproc clusters for distributed data processing using Apache Spark or PySpark Should have experience deploying models and services using Vertex AI, Cloud Run, or Cloud Functions Should be comfortable working with BM25 ranking (via Elasticsearch or OpenSearch) and blending with vector-based approaches Good to have: Familiarity with Vertex AI Matching Engine for scalable vector retrieval Good to have: Familiarity with TensorFlow Hub, Hugging Face, or other model repositories Good to have: Experience with prompt engineering, context windowing, and embedding optimization for LLM-based systems Should understand how to build end-to-end ML pipelines for search and ranking applications Must have: Awareness of evaluation metrics for search relevance (e.g., precision@k, recall, nDCG, MRR) Should have exposure to CI/CD pipelines and model versioning practices GCP Tools Experience: ML & AI: Vertex AI, Vertex AI Matching Engine, AutoML, AI Platform Storage: BigQuery, Cloud Storage, Firestore Ingestion: Pub/Sub, Cloud Functions, Cloud Run Search: Vector Databases (e.g., Matching Engine, Qdrant on GKE), Elasticsearch/OpenSearch Compute: Cloud Run, Cloud Functions, Vertex Pipelines, Cloud Dataproc (Spark/PySpark) CI/CD & IaC: GitLab/GitHub Actions Location: Remote- Bengaluru,Hyderabad,Delhi / NCR,Chennai,Pune,Kolkata,Ahmedabad,Mumbai

Posted 2 months ago

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0.0 - 1.0 years

3 - 4 Lacs

Noida

Work from Office

Key Responsibilities: Assist in the design, development, and deployment of Python-based AI/ML models and applications. Work with senior developers and data scientists to preprocess data, train models, and evaluate performance. Write clean, scalable, and efficient Python code for automation, data analysis, and AI pipelines. Participate in brainstorming sessions, code reviews, and team meetings. Document project requirements, processes, and results. Required Skills: Strong foundation in Python programming. Basic understanding of Machine Learning concepts and algorithms. Familiarity with libraries such as NumPy, Pandas, Matplotlib, and scikit-learn. Good analytical and problem-solving skills. Willingness to learn new technologies and take initiative. Good to Have: Exposure to deep learning frameworks like TensorFlow or PyTorch. Experience with Jupyter Notebooks, Git/GitHub, or any version control system. Academic projects or internships related to AI/ML or Python development. Eligibility Criteria: B.E./B.Tech/MCA/M.Sc. in Computer Science, IT, or related field (2023/2024 pass-out preferred). Strong academic track record with a passion for AI and software development. What We Offer: Hands-on experience on real-world AI/ML projects. Mentorship and training by experienced professionals. Dynamic and collaborative work environment. Career growth opportunities in AI and software development domains.

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