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Who are we

Fulcrum Digital is an agile and next-generation digital accelerating company providing digital transformation and technology services right from ideation to implementation. These services have applicability across a variety of industries, including banking & financial services, insurance, retail, higher education, food, healthcare, and manufacturing.

About the Role

We are looking for a skilledand hands-on Data Scientist with 45 years of experience in developingand deploying machine learning modelsranging from traditional ML algorithms toadvanced deep learning and Generative AI systems. The ideal candidate brings astrong foundation in classification, anomaly detection, and time-seriesmodeling, along with hands-on experience in deploying and optimizing Transformer-basedmodels . Familiarity with quantization , fine-tuning , and RAG(Retrieval-Augmented Generation) is highly desirable.

Responsibilities

Design, train, and evaluate ML models for tasks such as classification, anomaly detection, forecasting, and natural language understanding.

Build and fine-tune deep learning models, including RNNs, GRUs, LSTMs , and Transformer architectures (e.g., BERT, T5, GPT).

Develop and deploy Generative AI solutions , including RAG pipelines for use cases such as document search, Q&A, and summarization.

Perform model optimization techniques such as quantization for improving latency and reducing memory/compute overhead in production.

Optionally fine-tune LLMs using Supervised Fine-Tuning (SFT) and Parameter-Efficient Fine-Tuning (PEFT) methods like LoRA or QLoRA .

Define and track relevant evaluation metrics; continuously monitor model drift and retrain models as needed.

Collaborate with cross-functional teams (data engineering, backend, DevOps) to productionize models using CI/CD pipelines.

Write clean, reproducible code and maintain proper versioning and documentation of experiments.

Requirements
Required Skills

45 years of hands-on experience in machine learning or data science roles.

Proficient in Python and ML/DL libraries: scikit-learn, pandas, PyTorch, TensorFlow.

Strong knowledge of traditional ML and deep learning, especially for sequence and NLP tasks.

Experience with Transformer models and open-source LLMs (e.g., Hugging Face Transformers).

Familiarity with Generative AI tools and RAG frameworks (e.g., LangChain, LlamaIndex).

Experience in model quantization (e.g., dynamic/static quantization, INT8) and deployment on constrained environments.

Knowledge of vector stores (e.g., FAISS, Pinecone, Azure AI Search), embeddings, and retrieval techniques.

Proficiency in evaluating models using statistical and business metrics.

Experience with model deployment , monitoring , and performance tuning in production environments.

Familiarity with Docker, MLflow, and CI/CD practices.

Preferred Qualifications

Experience fine-tuning LLMs (SFT, LoRA, QLoRA) on domain-specific datasets.

Exposure to MLOps platforms (e.g., SageMaker, Vertex AI, Kubeflow).

Familiarity with distributed data processing (e.g., Spark) and orchestration tools (e.g., Airflow).

Contributions to research papers, blog posts, or open-source projects in ML/NLP/GenAI.

" , "Job_Type":"Permanent" , "Job_Opening_Name":"Data Scientist / AI Engineer" , "State":"Maharashtra" , "Country":"India" , "Zip_Code":"411057" , "id":"613047000049295844" , "Publish":true , "Keep_on_Career_Site":false , "Date_Opened":"2025-10-14"}]

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Data Scientist / AI Engineer