Job Description:

• Application & System Building: Designing intelligent workflows, multi-agent systems, and functional applications powered by AI APIs. 
• Model Integration & Infrastructure: Converting machine learning models into clean Application Programming Interfaces (APIs) or microservices and deploying them to cloud platforms like AWS, Google Cloud, or Azure.
• Advanced Data Retrieval: Implementing Retrieval-Augmented Generation (RAG) pipelines using semantic embeddings and vector databases to link models with specific company data. 
• Data Processing & Pipelines: Building automated data pipelines to ingest, clean, and preprocess large unstructured datasets for model training and real-time inference. 
• System Optimization: Monitoring model performance, handling latency, minimizing compute costs, and fixing model drift or output degradation. 
• Prompt Engineering & Fine-tuning: Crafting advanced prompts and occasionally fine-tuning existing models on custom enterprise datasets to maximize output accuracy. 
• Ethical AI & Compliance: Safeguarding deployments by monitoring for bias, ensuring data privacy compliance (like GDPR), and maintaining system security. 

---

• Programming Languages: Highly proficient in Python, SQL, and sometimes Java, C++, or JavaScript.
• Frameworks & Orchestration: Deep hands-on experience with tools like LangChain, LlamaIndex, TensorFlow, PyTorch, and Hugging Face.
• Vector Databases: Familiarity with vector storage systems like Pinecone, Milvus, Chroma, or Weaviate.
• Cloud & MLOps Tools: Competency with Docker, Kubernetes, Git, MLflow, and specialized cloud AI workbenches (e.g., AWS SageMaker, Azure ML, or Vertex AI).
• Foundational Mathematics: A practical grasp of applied statistics, linear algebra, and calculus to troubleshoot model behavior.

• Cross-functional Collaboration: Acting as a liaison between data scientists, product managers, software developers, and corporate stakeholders.
• Analytical Problem Solving: Navigating rapid technical iterations and turning vague business problems into structured software code.
• Technological Watch: Maintaining a proactive curiosity to quickly absorb and apply new model releases and emerging frameworks.

Industry:

Human Resources

Category:

Recruitment

Skills: