Freelance Data Scientist
Leading MNC
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
Skills
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