AI/ML Data Scientist

Orcapod Consulting Services; Bengaluru; Hybrid; INR 2,400,000 - 4,200,000; Full time

Job summary

Orcapod Consulting Services seeks an experienced AI/ML Data Scientist (8–12 years) for designing, developing, and deploying ML and Generative AI solutions in Bangalore. The role emphasizes predictive modeling, NLP, MLOps, and cloud platforms to deliver scalable business outcomes.

You will build end-to-end ML pipelines, collaborate with stakeholders, and mentor junior practitioners while staying current with GenAI trends in a fast-paced environment.

Qualifications

• Bachelor's or Master's degree in CS/DS/Math/AI or related field.
• 8–12 years of experience in DS/AI/ML.
• Strong hands-on Python and ML frameworks.
• Production deployment of AI/ML models.
• Solid grasp of statistics, probability and data modeling.
• Experience in Agile/Scrum environments.
• Excellent communication and stakeholder management.

Responsibilities

• Design, develop, and deploy ML/AI models for business problems.
• Build predictive, classification, forecasting, and recommender systems.
• Analyze structured and unstructured data to derive insights.
• Develop Generative AI, LLM, and NLP solutions.
• Perform feature engineering, model selection and hyperparameter tuning.
• Build scalable AI pipelines and production ML solutions.
• Collaborate with business to translate requirements into DS solutions.
• Implement MLOps for deployment, monitoring and governance.
• Mentor junior data scientists and ML engineers.
• Stay updated with AI and GenAI trends.

Skills

Python

SQL

PySpark

Pandas

NumPy

Scikit-learn

Supervised Learning

Unsupervised Learning

Time Series Forecasting

Recommendation Systems

Statistical Modeling

Transformers

NLP

Big Data

Cloud Platforms

MLOps

Docker

Kubernetes

Git

Education

Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, AI, or related field

Tools

Python

SQL Server

PostgreSQL

MySQL

MongoDB

Vector Databases (Pinecone, FAISS, ChromaDB)

Apache Spark

Databricks

Hadoop Ecosystem

Kafka

AWS SageMaker

Azure AI Services

Google Vertex AI

MLflow

Kubeflow

Docker

Kubernetes

Job description

Role & responsibilities - Immediate Joiner( Relocation Possible )

Job Description AI/ML Data Scientist (8 to 12 Years Experience)

Position

AI/ML Data Scientist

Experience

8 to 12 Years

Location

Bangalore

Notice Period

Immediate to 20 Days Preferred

Job Summary

We are seeking a highly skilled AI/ML Data Scientist with 8 to 12 years of experience in designing, developing, and deploying Machine Learning and Generative AI solutions. The ideal candidate will have strong expertise in data science, predictive modeling, deep learning, NLP, MLOps, and cloud-based AI platforms to deliver business-driven AI solutions at scale.

Key Responsibilities

• Design, develop, and deploy Machine Learning and AI models for real-world business problems.
• Build predictive, classification, recommendation, forecasting, and optimization models.
• Analyze structured and unstructured datasets to derive actionable insights.
• Develop and implement Generative AI, LLM, and NLP-based solutions.
• Perform feature engineering, model selection, hyperparameter tuning, and performance optimization.
• Build scalable AI pipelines and production-ready ML solutions.
• Collaborate with business stakeholders to translate business requirements into data science solutions.
• Implement MLOps practices for model deployment, monitoring, and governance.
• Mentor junior data scientists and ML engineers.
• Stay updated with emerging AI, GenAI, LLM, and Data Science trends.

Required Technical Skills

Programming & Data Handling

• Python
• SQL
• PySpark
• Pandas
• NumPy
• Scikit-learn

Machine Learning

• Supervised Learning
• Unsupervised Learning
• Ensemble Techniques
• Time Series Forecasting
• Recommendation Systems
• Statistical Modeling

Deep Learning

• TensorFlow
• PyTorch
• Keras
• CNN
• RNN
• Transformers

Generative AI & LLMs

• OpenAI
• Azure OpenAI
• LangChain
• LangGraph
• RAG (Retrieval-Augmented Generation)
• Prompt Engineering
• Fine-Tuning LLMs
• Vector Databases

NLP

• NLTK
• SpaCy
• Hugging Face
• Text Classification
• Named Entity Recognition (NER)
• Sentiment Analysis
• Conversational AI

Big Data Technologies

• Apache Spark
• Databricks
• Hadoop Ecosystem
• Kafka

Cloud Platforms

• AWS (SageMaker, S3, Lambda)
• Azure AI Services
• Google Vertex AI

MLOps & Deployment

• MLflow
• Kubeflow
• Docker
• Kubernetes
• CI/CD Pipelines
• Model Monitoring
• Git

Databases

• SQL Server
• PostgreSQL
• MySQL
• MongoDB
• Vector Databases (Pinecone, FAISS, ChromaDB)

Leadership Responsibilities

• Lead AI/ML solution architecture and technical design discussions.
• Drive end-to-end model development lifecycle.
• Mentor and guide Data Scientists and ML Engineers.
• Review model performance, scalability, and deployment strategies.
• Work closely with Product, Engineering, and Business teams.
• Define AI best practices, governance, and model validation standards.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, AI, or related field.
• 812 years of experience in Data Science, Machine Learning, and AI solutions.
• Strong hands-on expertise in Python and ML frameworks.
• Experience deploying AI/ML models to production environments.
• Strong understanding of statistics, probability, and data modeling.
• Experience working in Agile/Scrum environments.
• Excellent communication and stakeholder management skills.

Good to Have

• Experience with Multi-Agent AI Systems.
• Exposure to AI Governance and Responsible AI.
• Hands-on experience with LLM Fine-Tuning and RAG Architectures.
• Cloud AI/ML Certifications (AWS, Azure, GCP).
• Knowledge of Graph AI and Knowledge Graphs.

Keywords

AI, Machine Learning, Data Scientist, Generative AI, GenAI, LLM, GPT, LangChain, LangGraph, RAG, Python, PyTorch, TensorFlow, NLP, Deep Learning, MLOps, Databricks, Spark, Azure OpenAI, AWS SageMaker, Vector Database, MLflow, Predictive Analytics, Data Science, AI Solutions, Feature Engineering, Model Deployment.