AI/ML Engineers

5 days ago

Mohali, India Outline Systems Full time

.Overall Focus: Designing, developing, training, deploying, and maintaining AI/ML models, encompassing both classical machine learning techniques and advanced Generative AI/Large Language Models (LLMs).

  • General Responsibilities (Applicable to all AI/ML Engineers):

  • Data preprocessing, feature engineering, model selection, and rigorous hyperparameter tuning.

  • Developing robust and scalable APIs for AI/ML model consumption and integration.
  • Implementing MLOps practices for model monitoring, performance tracking, and automated retraining strategies.

  • Continuously researching and applying advancements in the AI/ML field to project work

  • Required Specialized Skill Sets & Experience:

  • A. Classical Machine Learning (Essential expertise):

  • Deep practical expertise in algorithms such as regression, classification, clustering, anomaly detection, dimensionality reduction, time series analysis, etc.

  • Strong statistical foundation, experimental design, and model evaluation techniques (e.g., cross-validation, precision/recall, ROC/AUC, F1-score).

  • B. Generative AI & LLMs (Essential expertise):

  • Core GenAI Development:

  • Proficiency with open-source GenAI frameworks and libraries (e.g., Hugging Face Transformers, LlamaIndex, Langchain, FAISS).

  • Deep experience in developing and fine-tuning RAG (Retrieval Augmented Generation) based GenAI solutions.

  • Hands-on experience architecting and utilizing major cloud-based GenAI platforms (e.g., AWS Bedrock, Azure OpenAI Service, Google Vertex AI).

  • Applied GenAI Capabilities:

  • Leveraging various GenAI models for tasks such as:

  • Text Processing: Advanced summarization, complex question answering, nuanced text generation, semantic search, knowledge extraction, and high-quality embedding generation.

  • Image Processing (as relevant): Image generation/manipulation, content analysis, object recognition leveraging foundation models.

  • Video Processing (as relevant): Video content analysis, summarization, event detection using GenAI approaches.

  • Fundamental GenAI Understanding:

  • Thorough understanding and practical strategies for addressing bias and hallucination in LLMs.

  • Expertise in vector embeddings, various similarity comparison techniques (e.g., cosine similarity, dot product), and the practical differences between keyword-based vs. semantic search.

  • C. Essential Cross-Cutting Experience (Relevant across the AI/ML team):

  • Document Management & Processing:

  • Strong experience with advanced OCR technologies and document digitization workflows.

  • Proven ability in information extraction from diverse document types (structured, semi-structured, unstructured PDFs, images) and document understanding using ML/AI techniques.

  • D. Desirable (Good to Have) Experience:

  • Agentic AI Experience designing or implementing AI agents or multi-agent systems.

  • MCP (Model Compliance/Criticality/Card Platform - please specify if this means something else in your context ) Relevant Project Experience: Experience aiwith platforms or processes for model governance, documentation, risk assessment, or similar.

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