Vacancy description
Coffeebeans.io - Generative AI Engineer in Hyderabad, भारत
CoffeeBeans
Hyderabad, भारत
About the job : About CoffeeBeans Consulting : CoffeeBeans is a tech-driven software consulting company that helps businesses solve complex problems using modern data, AI, and engineering solutions. We blend deep technical expertise with a product mindset to build scalable, intelligent, and high-impact solutions across industries. Our data science team works on end-to-end delivery from exploration and modeling to GenAI application development and https://jobeax.com/link/mJ78hVmWIf2q1LBW : 3 - 5 YearsLocation : Hyderabad | Work mode : Work from Office (5 Days)Role Overview : As an L2 Data Scientist, you will play a hands-on role in delivering production-grade ML and GenAI-powered applications. You are expected to independently take ownership of data science components within client projects, contribute to solutioning and design, and mentor junior team members. You will work across a range of use cases such as personalization, fraud detection, intelligent automation, RAG pipelines, and LLM-based assistants. This role is ideal for someone who has proven experience in both traditional ML and an emerging understanding of LLMs and generative AI https://jobeax.com/link/wXURIxgrAfa888Pf Responsibilities : ML & Data Science : - Own and deliver ML model development, tuning, and evaluation for client-facing projects.- Lead exploratory data analysis, data preprocessing, and feature engineering with minimal supervision.- Build models using appropriate ML techniques (classification, regression, clustering, recommendation) and ensure performance meets business expectations.- Contribute to experimentation frameworks and model reproducibility best https://jobeax.com/link/WjiQ0ePQYEkiOAG1 & LLM Applications : - Design and prototype GenAI solutions using LLMs (e.g., OpenAI, Claude, Mistral, Llama).- Hands-on experience with AgenticAI.- Build RAG pipelines, prompt templates, few-shot learning prompts, and evaluation mechanisms for GenAI systems.- Integrate LLMs with APIs, vector databases (e.g., Pinecone, FAISS, Weaviate), and context providers.- Contribute to benchmarking, safety, and cost-performance trade-offs in LLM app https://jobeax.com/link/KsRyp0GYZdHSczIw & Engineering Collaboration : - Collaborate with engineering teams to take models from experimentation to deployment (batch/real-time).- Assist in building APIs and data pipelines needed for productionizing models.- Contribute to technical documentation, explainability reports, and client https://jobeax.com/link/S7alBjuu0jIALJfA & Growth : - Mentor junior data scientists and review code/model design.- Stay current with advances in ML and GenAI to inform solution design and share knowledge internally.- Participate in discovery and solutioning phases with clients alongside tech leads and https://jobeax.com/link/x5yiJxpaJlNyweJ3 Skills & Qualifications : - Bachelors or Masters degree in Computer Science, Data Science, Engineering, Statistics, or a related field.- 2 - 5 years of hands-on experience in applied data science, including both ML model development and GenAI-based solutioning.- Strong command over Python and ML libraries (scikit-learn, XGBoost, LightGBM, etc.).- Experience working with LLM APIs (OpenAI, Cohere, Claude, etc.) and frameworks (LangChain, LlamaIndex, or similar).- Hands-on experience with prompt engineering, RAG workflows, and evaluating LLM outputs.- Proficiency in SQL and data wrangling tools (pandas, NumPy).- Experience working with REST APIs, Git, and cloud environments (AWS/GCP).Good-to-Have Skills : - Experience with deploying models via FastAPI, Docker, or serverless platforms.- Knowledge of MLOps tools (MLflow, DVC) and monitoring frameworks.- Experience with embeddings, vector databases, and similarity https://jobeax.com/link/oYuhnknhp0hi0z14 You Can Expect at CoffeeBeans : - Work on real-world AI/ML problems across verticals.- Be part of a fast-moving team delivering end-to-end ML & GenAI apps.- Collaborate with experienced engineers and PMs in a flat and open culture.- Opportunities to lead, mentor, and influence tech direction. (ref:hirist.tech)