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 skilled and hands-on
Data Scientist
with 4-5 years of experience in developing and deploying machine learning models--ranging from traditional ML algorithms to advanced deep learning and Generative AI systems. The ideal candidate brings a strong foundation in classification, anomaly detection, and time-series modeling, along with hands-on experience in deploying and optimizing
Transformer-based models
. 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
4-5 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 Opening ID
RRF_5985
Job Type
Permanent
Industry
IT Services
Date Opened
14/10/2025
City
Pune City
Province
Maharashtra
Country
India
Postal Code
411057
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