Ai Developer With Deep Learning Nlp And Full Stack Capability At Paraslabs

## About the role We work closely with client teams across the entire AI adoption journey, from AI-curious organizations to AI-native businesses, with a strong focus on delivering measurable outcomes. Most of our engagements involve applied AI in real production environments. We value people who are comfortable operating in ambiguity, take ownership, and move things forward proactively. We are looking for hands-on AI Developers who can build and ship production-grade systems. In this role, you will design, develop, and integrate AI/ML solutions across client engagements, collaborating with architects, engineers, and designers to solve real business problems. The systems you build will be deployed and used in production environments, not just presented in slides or prototypes. The candidate must show equal interest as a software engineer to work on both. ## Key Responsibilities - Develop and integrate various AI/ML models into production applications and APIs across client engagements. - Build and maintain RAG pipelines using LLMs with vector databases; implement prompt engineering strategies, chain-of-thought workflows, and agentic AI patterns. - Work directly with clients across industries (real estate, enterprise, manufacturing, automation) to translate business problems into working AI solutions. - Develop data pre-processing, feature engineering, and model evaluation pipelines. - Convert research papers and emerging techniques into usable, production-ready models. - Write clean, well-tested, and maintainable code following the studio's engineering standards. - Participate in code reviews, sprint ceremonies, and technical design discussions alongside AI Architects and engineers. - Monitor deployed AI systems, debug issues, and implement performance improvements. - Stay current with rapidly evolving AI frameworks, open source models, and best practices — and bring what is useful back into the studio's work. - Contribute to thought leadership, internal tooling, and IP that reflects how we think about AI. ## Required Qualifications - 2+ years of software development experience with 1+ years focused on AI/ML development. - Full Stack - Strong Python skills; proficiency with ML libraries (NumPy, Pandas, scikit-learn, Hugging Face Transformers). - Hands-on experience with LLMs (GPT-VX, Claude, Llama, Mistral and open source models) and orchestration frameworks such as LangChain, LlamaIndex, or Semantic Kernel. - Proven experience building RAG systems, vector databases (Pinecone, Weaviate, Azure AI Search), and embeddings pipelines. - Familiarity with cloud AI services: Azure OpenAI, AWS Bedrock, or Google Vertex AI. - Solid understanding of REST API development (FastAPI, Flask, or Django). - Able to work comfortably in a consulting/studio environment, multi-client, fast-context-switching, outcome-focused. - Strong communicator, able to discuss AI implementation clearly with both technical and non-technical stakeholders. - Comfortable working in a dynamic, start-up environment where the work evolves quickly. ## Preferred Qualifications - Experience with fine-tuning, RLHF workflows, or converting research papers into usable models. - Exposure to multi-modal AI (vision, speech, document intelligence) relevant to industrial and enterprise client base. - Familiarity with predictive maintenance, anomaly detection, or industrial AI systems. - Knowledge of containerisation (Docker) and CI/CD pipelines. - Background in Agile or iterative delivery environments; comfortable with short cycles and visible progress. - Experience working in or alongside GCC or embedded team models. - Exposure to IOT , OT Systems is a big plus ## Application Instructions Please mention your github repository and links to other technical papers /contributions. Please note: This is not an Internship type role and it's not for students, still studying?