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AI-ML Tech Engineer

AI-ML Tech Engineer

ConfidentialPune
1 day ago
Job description

Job Overview

We are seeking an AI-ML Tech Engineer with a strong background in machine learning, data science, and software engineering. The ideal candidate will have experience in developing and deploying machine learning models, handling large datasets, and collaborating with cross-functional teams to solve real-world challenges.

Key Responsibilities

  • Develop and deploy machine learning and NLP solutions using common ML libraries and frameworks.
  • Work with large datasets and distributed computing systems to extract meaningful insights.
  • Fine-tune deep learning models, including large language models (LLMs) and small language models (SLMs).
  • Implement and optimize ML pipelines for training, evaluation, and inference.
  • Utilize AI cloud services for efficient model deployment and management.
  • Develop and maintain CI / CD pipelines for ML training and deployment.
  • Work on AI-powered solutions involving Vector Stores and Retrieval-Augmented Generation (RAG) pipelines.
  • Translate ML-based outcomes into business-digestible insights.
  • Collaborate with stakeholders to define project requirements and deliver innovative AI solutions.

Mandatory Skills & Qualifications

  • Expertise in Python and ML frameworks (TensorFlow, PyTorch, Keras, Scikit-learn).
  • Strong understanding of statistical models, regression, clustering, and ML algorithms (e.g., decision trees, Random Forests, neural networks).
  • Experience in deploying ML models in production environments.
  • Proficiency in cloud AI services (AWS, Azure, or GCP).
  • Knowledge of large language models like OpenAI's GPT-3.5, GPT-4, and Codex.
  • Hands-on experience with vector databases and RAG-based ML solutions.
  • Proficient in various ML deployment strategies, both static and dynamic.
  • Experience in MLOps, automation, and CI / CD pipelines for ML workflows.
  • Excellent communication skills and experience managing stakeholders.
  • Nice-to-Have Skills

  • Experience with MLOps tools for continuous integration and deployment.
  • Knowledge of full-stack development and API frameworks (Flask, Django).
  • Familiarity with Databricks, Data Mesh, and ETL pipelines.
  • Hands-on experience with Docker containers.
  • Exposure to agile methodologies such as Scrum or Kanban, and project management tools like JIRA / GitLab.
  • Skills Required

    Django, Pytorch, Flask, Databricks

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