V
Data Scientist
Job Description
We are seeking a Data Scientist with 3–6 years of experience to design, build, and deploy GenAI and LLM-powered solutions. The role combines applied ML, prompt engineering, and MLOps to deliver scalable, production-grade AI systems.
Key Responsibilities
Develop and deploy LLM-based applications (RAG, chatbots, copilots, summarization, search)
Fine-tune, evaluate, and optimize LLMs and transformer models
Design prompt engineering strategies and guardrails for safe, reliable outputs
Build retrieval pipelines using vector databases (FAISS, Pinecone, etc.)
Implement end-to-end ML pipelines (data → model → deployment → monitoring)
Collaborate with engineering teams to integrate models via APIs and microservices
Monitor model performance, drift, and costs; implement feedback loops
Ensure responsible AI practices (bias mitigation, explainability, governance)
Required Skills & Qualifications
3–6 years of experience in Data Science / ML Engineering / Applied AI
Strong programming in Python
Hands-on experience with LLMs (OpenAI, Azure OpenAI, etc.)
Experience with transformers, embeddings, and NLP pipelines
Familiarity with RAG architectures and vector search
Solid foundation in ML algorithms, statistics, and evaluation metrics
Strong SQL and data handling skills
MLOps & Engineering Skills
Experience with model deployment (FastAPI, Flask, Docker, Kubernetes)
Exposure to CI/CD pipelines for ML (GitHub Actions, Azure ML, SageMaker, etc.)
Experience in model monitoring, logging, and versioning (MLflow, Weights & Biases)
Knowledge of data pipelines (Airflow, Spark)
Familiarity with cloud platforms (AWS, Azure, or GCP)
Preferred Qualifications
Experience fine-tuning LLMs (LoRA, PEFT techniques)
Exposure to multi-modal models (text + image/audio)
Knowledge of AI safety, hallucination mitigation, and evaluation frameworks
Domain experience in enterprise use cases (support, search, analytics, automation)
Soft Skills
Strong problem-solving and experimental mindset
Ability to translate ambiguous business problems into AI solutions
Excellent communication with technical & non-technical stakeholders
Education
Bachelor's or Master's in Computer Science, AI, Data Science, Statistics, or a related field
Key Responsibilities
Develop and deploy LLM-based applications (RAG, chatbots, copilots, summarization, search)
Fine-tune, evaluate, and optimize LLMs and transformer models
Design prompt engineering strategies and guardrails for safe, reliable outputs
Build retrieval pipelines using vector databases (FAISS, Pinecone, etc.)
Implement end-to-end ML pipelines (data → model → deployment → monitoring)
Collaborate with engineering teams to integrate models via APIs and microservices
Monitor model performance, drift, and costs; implement feedback loops
Ensure responsible AI practices (bias mitigation, explainability, governance)
Required Skills & Qualifications
3–6 years of experience in Data Science / ML Engineering / Applied AI
Strong programming in Python
Hands-on experience with LLMs (OpenAI, Azure OpenAI, etc.)
Experience with transformers, embeddings, and NLP pipelines
Familiarity with RAG architectures and vector search
Solid foundation in ML algorithms, statistics, and evaluation metrics
Strong SQL and data handling skills
MLOps & Engineering Skills
Experience with model deployment (FastAPI, Flask, Docker, Kubernetes)
Exposure to CI/CD pipelines for ML (GitHub Actions, Azure ML, SageMaker, etc.)
Experience in model monitoring, logging, and versioning (MLflow, Weights & Biases)
Knowledge of data pipelines (Airflow, Spark)
Familiarity with cloud platforms (AWS, Azure, or GCP)
Preferred Qualifications
Experience fine-tuning LLMs (LoRA, PEFT techniques)
Exposure to multi-modal models (text + image/audio)
Knowledge of AI safety, hallucination mitigation, and evaluation frameworks
Domain experience in enterprise use cases (support, search, analytics, automation)
Soft Skills
Strong problem-solving and experimental mindset
Ability to translate ambiguous business problems into AI solutions
Excellent communication with technical & non-technical stakeholders
Education
Bachelor's or Master's in Computer Science, AI, Data Science, Statistics, or a related field
More Info
Key Skills
vector search
embeddings
data pipelines
MLflow
Azure OpenAI
GitHub Actions
NLP pipelines
RAG architectures
Weights Biases
LLMs
ML algorithms
MLOps Engineering
SageMaker
CI CD pipelines
OpenAI
evaluation metrics
About Company
Skills:
Time Series, Clustering, Sql, Logistic Regression, Excel, Kubernetes, Decision Trees, Feature selection, Regression, Boosting, Regularization techniques, Statistical Techniques
Skills:
probability , Text Analytics, Machine Learning, Artificial Intelligence, Deep Learning, Tensorflow, Pytorch, Keras, Python, Computer Vision, Generative AI, Statistics, linear algebra
Skills:
Predictive Modeling, Amazon Web Services, Requirements Analysis, Agile Software Development, Data Mining, Big Data, Microsoft Azure, Programming, SQL query language, Statistical Modeling
Skills:
Data Transformation, Python Programming, logic-based workflows, data pipeline development, SQL proficiency, Dataiku, analytics and data manipulation competencies, Excel-like analytical methods
Skills:
Machine Learning, Nlp, Opencv, Keras, Predictive Analytics, Python, Tensorflow, Cv