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GOLS Private Limited
Associate AI/ML Engineer Product AI & Generative AI
GOLS Private Limited
Mumbai•On-site•1-4 Yrs•Jun 16
Job description
Overview
We are looking for an enthusiastic AI/ML Engineer with 1-3 years of experience to work on AI-powered product features across enterprise platforms.
Responsibilities
- Develop AI/ML and Generative AI features for enterprise products using Python.
- Build and enhance AI-driven product modules such as chatbots, AI assistants, recommendation engines, document search, resume generation, and workflow automation.
- Design, develop, and maintain backend services and REST APIs using FastAPI.
- Build integrations between AI services and existing business systems, internal platforms, LMS/HRMS products, databases, and third-party APIs.
- Work with structured and unstructured data including documents, PDFs, spreadsheets, text, and user activity data.
- Perform data cleaning, preprocessing, feature engineering, and transformation using Pandas and NumPy.
- Create and optimise machine learning models using Scikit-Learn, TensorFlow, or PyTorch.
- Build Generative AI solutions using LLMs for content generation, Q&A systems, summarisation, knowledge assistants, and intelligent search.
- Help build simple Retrieval-Augmented Generation (RAG) workflows for enterprise documents and knowledge bases.
- Implement prompt engineering, prompt testing, prompt templates, and guardrails for LLM-based applications.
- Follow data privacy, security, and responsible AI practices while working with resumes, user data, enterprise documents, and LMS/HRMS information.
- Collaborate closely with product managers, QA teams, and developers to convert product ideas into working AI features.
- Strong hands-on programming skills in Python (mandatory).
- Good understanding of Object-Oriented Programming (OOP), basic data structures, and API development in Python.
Qualifications
- Hands-on knowledge of Pandas, NumPy, and Scikit-Learn.
- Basic exposure to TensorFlow or PyTorch.
- Understanding of core machine learning concepts including supervised and unsupervised learning, classification, regression, model evaluation, feature engineering, and data preprocessing.
- Basic understanding of Generative AI and Large Language Models (LLMs).
- Familiarity with the basic concepts of Retrieval-Augmented Generation (RAG), embeddings, and vector search.
- Familiarity with prompt engineering and prompt optimisation.
- Good understanding of JSON, REST APIs, authentication, and API integrations.
- Working knowledge of SQL and Git/version control.
- Strong analytical thinking, debugging, problem-solving, and communication skills.
- Exposure to vector databases such as FAISS, Chroma, Pinecone, Weaviate, or Milvus.
- Familiarity with additional frameworks such as LlamaIndex.
- Exposure to prompt evaluation, testing, or observability tools such as LangSmith is a plus.
- Basic understanding of Docker, cloud platforms (AWS, Azure, or GCP), and deployment concepts.
- Awareness of MLOps concepts such as model versioning, monitoring, CI/CD, or experiment tracking.
- Familiarity with Postman, Swagger, Jupyter Notebook, and VS Code.
- Exposure to OCR, NLP libraries, document parsing, or semantic search.
- Basic frontend understanding (HTML, JavaScript, React) is a plus but not mandatory.
- Candidates with relevant internships, live projects, freelance work, hackathons, or strong GitHub portfolios may also be considered.