Remote India Data scientist Jobs – 141 Open Jobs Today

Data Scientist Gen AI
HR Central —Remote
- ₹30,00,000 - ₹40,00,000 a year
- Full-time
- Remote
- Master's degree
- Databases
- SQL
Quick apply
12d
AI/ML Engineer
Placement Services —Remote
- ₹3,71,576.93 - ₹5,40,000.00 a year
- Full-time
- Remote
- Master's degree
- AI
- Python
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Ai/Ml data Scraping Intern
Green Dream Earth —Remote
- ₹3,500 - ₹4,000 a month
- Remote
- Computer Science
- Java
- AI
- Paid time off
- Flexible schedule
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AI Developer – Agentic AI (Enterprise Systems) (WFH)
Outsource Bigdata —Remote
- Full-time
- Remote
- Computer Science
- System design
- Master's degree
- Work from home
Senior AI Engineer I
AxisMaxlife —Remote
- Remote
- Computer Science
- Master's degree
- Math

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AI/ML Engineer
Placement Services —Remote
Additional Opportunities:Certification and client interview opportunities for eligible candidates are also available. Claude AI & AI-powered workflows.
₹3,71,576.93 - ₹5,40,000.00 a year
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Software Engineer – AI/ML
Revolite Infotech Pvt. Ltd —Remote
We are looking for an experienced *Software Engineer – AI/ML* to design, develop, and deploy scalable machine learning solutions within the *AWS environment*.
Up to ₹16,00,000 a year
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Data Scientist Gen AI

HR Central -
Remote

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Job details

Permanent | Full-time
₹30,00,000 - ₹40,00,000 a year
12 days ago

Qualifications

CI/CD
Law
MCP
Kubernetes
Software deployment
NumPy
Git
Master's degree
Databases
SQL
Pandas
Docker
Machine learning
Continuous integration
SDKs
REST
APIs
Data science
Manufacturing
AI
gRPC
Graph databases
Python

Full job description

Exp - 8+ years of progressive experience in data science and machine learning, with a minimum of 3 years focused on Generative AI and LLM-based systems.

Demonstrated track record of delivering AI solutions at enterprise scale Hands-on experience with full AI/ML lifecycle management: data engineering, feature stores, model training, evaluation, deployment, and monitoring.Industry experience especially in Manufacturing Function in a Building Material Industry, Manufacturing, Process or Pharma is preferred.

Required skills:Proficiency in Python; strong working knowledge of relevant libraries & frameworks: LangChain, LangGraph, HuggingFace Transformers, PyTorch, scikit-learn, Pandas, and NumPy.

Deep experience with LLM APIs (OpenAI, Anthropic, Google, Mistral) and open-source model deployment via Ollama, vLLM, or TGI.

Solid command of vector databases, semantic search, and knowledge graph technologies for enterprise RAG architectures.

Proficiency with MLOps tooling: MLflow, Weights & Biases, Kubeflow, or similar; experience with LLMOps tools such as LangSmith.

Strong SQL and experience with modern data platforms such as Databricks for AI-ready data preparation.

Understanding of software engineering best practices: version control (Git), containerization (Docker/Kubernetes), API design (REST/gRPC), and CI/CD pipelines.

Knowledge of how to benchmark GenAI models beyond simple accuracy (e.g., toxicity, bias, and reasoning depth).

Exposure to multi-modal AI systems incorporating vision, audio, or structured document understanding (PDFs, tables, charts).

Good understanding of the GENAI standards (MCP, A2A, A2UI etc.)

Key Responsibilities:

Platform Prototyping: Design and implement core ML components, such as feature stores, model registries, and automated evaluation pipelines.

Standardization: Establish best practices for the ML lifecycle, from data labeling and experimentation to CI/CD for ML (MLOps).

Scalability: Optimize model inference and training workflows to handle high-throughput, low-latency requirements.

Internal Consulting: Act as a subject matter expert for product-facing data science teams, helping them leverage platform tools to solve complex business problems.

Tooling & Automation: Build internal libraries and SDKs that simplify the transition from a local research environment to a distributed production environment.

RAG Infrastructure: Design and optimize high-performance retrieval systems using vector databases (e.g., Pinecone, Weaviate) and advanced semantic search techniques.

LLM Evaluation Frameworks: Build automated "vibe-check" replacements. Develop rigorous evaluation pipelines using LLM-as-a-judge, G-Eval, or custom scoring rubrics to measure hallucination, faithfulness, and relevancy.

Agentic Orchestration: Develop and standardize the use of agentic frameworks (e.g., LangGraph, CrewAI) to allow product teams to build complex, multi-step AI workflows.

Model Lifecycle Management: Manage the transition between model providers (OpenAI, Anthropic, Google) and open-source alternatives (Llama 3+, Mistral) through unified abstraction layers.

Cost & Latency Optimization: Implement caching strategies (e.g., GPTCache), prompt compression, and token-usage monitoring to ensure the platform remains economically viable.

Guardrails & Safety: Integrate real-time content filtering and PII masking to ensure all LLM outputs comply with corporate security and ethical standards.

Pay: ₹3,000,000.00 - ₹4,000,000.00 per year

Work Location: Remote

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data scientist jobs in remote india

Data Scientist Gen AI

AI/ML Engineer

Ai/Ml data Scraping Intern

AI Developer – Agentic AI (Enterprise Systems) (WFH)

Senior AI Engineer I

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