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Freelance Data Scientist

Leading MNC

Remote · India Full-time Mid Level Yesterday

About the role

Job Overview

We are looking for an experience Freelance Data Scientist to join a high-performing engineering team working on scalable products for global enterprise clients.

This role is ideal for professionals currently working in a 100% REMOTE setup and looking to take up a long-term freelance or part-time engagement alongside their primary role with competitive compensation and meaningful additional income.

Company Background

We are a product engineering firm partnering with top-tier global organizations across consulting, fintech, retail, and consumer tech. Our 750+ strong engineering team delivers high-impact solutions across Product and Data Engineering, with deep expertise in Agentic AI, GenAI, RPA, and Full-stack development.

Key Responsibilities

  • Design and develop AI/ML models and intelligent systems for real-world applications.
  • Build and integrate LLM-based applications using modern AI frameworks.
  • Design AI-driven system architectures, ensuring scalability and performance.
  • Develop and manage knowledge graphs to represent complex data relationships.
  • Work with ontology modeling for structured knowledge representation.
  • Integrate machine learning models with production systems and APIs.
  • Evaluate model performance, system design trade-offs, and optimization strategies.
  • Collaborate with engineering, data, and product teams to implement AI solutions.
  • Contribute to AI architecture discussions and technical design decisions.

Required Skills & Experience

  • Strong understanding of Machine Learning and Deep Learning concepts.
  • Hands-on experience working with Large Language Models (LLMs).
  • Experience building AI-powered applications or intelligent systems.
  • Knowledge of Knowledge Graphs and Graph-based data modeling.
  • Experience with Ontology design and semantic data modeling.
  • Familiarity with AI frameworks such as PyTorch, TensorFlow, or similar.
  • Strong understanding of system architecture and design principles for AI systems.
  • Ability to reason through implementation trade-offs and scalability considerations.
  • Strong problem-solving and analytical skills.

Preferred Skills

  • Experience with LLM orchestration frameworks (LangChain, LlamaIndex, etc.).
  • Familiarity with Graph Databases (Neo4j, RDF stores, etc.).
  • Experience in semantic web technologies (RDF, OWL, SPARQL).
  • Experience deploying AI models in production environments.
  • Exposure to vector databases and retrieval-augmented generation (RAG).

Engagement Details

  • Commitment: ~35 hours per week with predictable workload and clear deliverables
  • Work Model: 100% remote engagement from our side
  • Compensation: Monthly payouts with a transparent pay cycle
  • Tenure: Long-term engagement for high performers; continuity and stability assured
  • Eligibility: Open only to professionals currently working in a full-time remote role (validated during screening)
  • Growth: Opportunity to work on complex, high-impact products alongside senior engineering leadership

Requirements

  • Strong understanding of Machine Learning and Deep Learning concepts
  • Hands‑on experience working with Large Language Models (LLMs)
  • Experience building AI‑powered applications or intelligent systems
  • Knowledge of Knowledge Graphs and graph‑based data modeling
  • Experience with ontology design and semantic data modeling
  • Familiarity with AI frameworks such as PyTorch, TensorFlow, or similar
  • Strong understanding of system architecture and design principles for AI systems
  • Ability to reason through implementation trade‑offs and scalability considerations
  • Strong problem‑solving and analytical skills

Responsibilities

  • Design and develop AI/ML models and intelligent systems for real‑world applications
  • Build and integrate LLM‑based applications using modern AI frameworks
  • Design AI‑driven system architectures, ensuring scalability and performance
  • Develop and manage knowledge graphs to represent complex data relationships
  • Work with ontology modeling for structured knowledge representation
  • Integrate machine learning models with production systems and APIs
  • Evaluate model performance, system design trade‑offs, and optimization strategies
  • Collaborate with engineering, data, and product teams to implement AI solutions
  • Contribute to AI architecture discussions and technical design decisions

Benefits

Long‑term engagementOpportunity to work on complex, high‑impact productsCollaboration with senior engineering leadership

Skills

Machine LearningDeep LearningLarge Language Models (LLMs)AI/ML model developmentKnowledge GraphsOntology modelingPyTorchTensorFlowSystem architecture designAPI integration

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