Senior - Consultant

7 days ago

India Emids Technologies Full time US$ 90,000 - US$ 1,20,000 per year

You'll be a core member of our AI team, designing, implementing, and optimizing GenAI applications for live, real-time deployments. Our projects frequently involve prompt engineering, vector databases, frameworks like LangChain, Langraph, and agentic tools such as AutoGen and Crew. You'll help build production-ready solutions for tasks like text generation, summarization, and Q&A systems—often within a cloud environment like Azure, AWS and/or GCP.

Responsibilities

  • Advanced Python Proficiency: Write clean, efficient, and maintainable Python code for data preprocessing, model training, and integration with production systems.
  • Prompt Engineering: Design, test, and refine prompts to produce optimal AI-driven outputs (chatbots, content generation, etc.).
  • Retrieval-Augmented Generation (RAG): Implement techniques that combine model outputs with external data sources to improve accuracy in real-world scenarios.
  • LangChain & Langraph Integration: Leverage these libraries to build modular, scalable AI pipelines for language-based tasks.
  • Vector Database Management: Work with databases like Pinecone, Faiss, or other vector stores to store embeddings and enable efficient semantic search.
  • Chunking Techniques: Develop methods to split large documents into manageable sections, ensuring more accurate and efficient retrieval and generation.
  • Streamlit (or Similar) Prototyping: Create user-facing dashboards or internal tools to visualize and interact with AI functionalities.
  • Metrics & Performance Tracking: Implement monitoring and logging solutions to track performance metrics (response time, accuracy, user engagement) and identify areas of improvement.
  • Collaboration & Documentation: Participate in code reviews, maintain thorough documentation, and share best practices with cross-functional teams.

What We're Looking For

  • Education: Bachelor's degree in Computer Science, Data Science, Engineering, or related field (or equivalent practical experience).
  • AI/ML Foundations: Familiarity with NLP, machine learning fundamentals, and deep learning frameworks (e.g., PyTorch or TensorFlow).
  • Programming Skills: Solid Python background; comfort with libraries like NumPy, pandas, and familiarity with concurrency or parallelism is a plus.
  • Hands-On Project Experience: Coursework or personal projects involving LLMs, vector databases, or text analysis; experience deploying real-time AI solutions is a bonus.
  • Cloud Familiarity: Exposure to either Azure or AWS; ability to learn how to set up virtual machines, container services, or serverless functions.
  • Adaptability: Excitement about experimenting with new libraries (LangChain, Langraph) and emerging large language models.
  • Curiosity & Team Spirit: Eagerness to learn, collaborate, iterate quickly, and stay current on GenAI trends.

Good to Have

  • Agentic Frameworks: Experience or interest in frameworks like AutoGen, Crew, or other agentic systems for automating AI-driven tasks.
  • MLOps & Tooling: Familiarity with containerization (Docker), CI/CD pipelines, or other DevOps practices for robust AI model deployment.
  • Advanced Python Libraries: Proficiency in data processing libraries (e.g., pandas, Dask) and knowledge of parallelization techniques.
  • Cloud Deployment: Use either Azure or AWS to configure and deploy AI models, ensuring scalability, security, and optimal performance for live applications.
  • Full-Stack Knowledge: Understanding of front-end technologies for better integration of AI-backed features in web or mobile interfaces.

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