AI/ML Engineer

4 years

0 Lacs

Posted:22 hours ago| Platform: Linkedin logo

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Work Mode

Remote

Job Type

Full Time

Job Description

Job Overview

AI/ML Engineer


Key Responsibilities

  • Assist in the design, development, and integration of AI/ML features into a SaaS application.
  • Work on training, fine-tuning, and deploying large language models (LLMs) with embedding techniques.
  • Develop Natural Language Processing (NLP) components, including tokenization, attention mechanisms, and sentiment analysis.
  • Implement AI tasks such as text summarization, semantic search, and basic supervised/unsupervised learning models.
  • Support optimization of AI/ML models through methods like quantization and pruning.
  • Contribute to creating searchable vector databases from structured and unstructured data.
  • Assist in building conversational AI solutions to improve user experience.
  • Collaborate with senior engineers and cross-functional teams to deliver AI-enabled features.
  • Monitor and test model performance, making improvements where necessary.


Required Skills and Experience

  • 2–4 years of hands-on experience in AI/ML software development.
  • Familiarity with LLMs and basic fine-tuning techniques.
  • Experience working with NLP frameworks and libraries (e.g., Hugging Face, spaCy, NLTK).
  • Understanding of sentiment analysis, text summarization, and semantic search concepts.
  • Basic knowledge of supervised and unsupervised learning approaches.
  • Proficiency in Python for AI/ML development.
  • Experience integrating AI models into applications.
  • Ability to work with APIs and build simple chatbot or conversational AI features.


Preferred Qualifications

  • Exposure to AI/ML applications in SaaS or cloud-based platforms.
  • Understanding of vector databases and embedding search.
  • Experience in agile or remote work environments.
  • Strong problem-solving and analytical skills.


Key Competencies

  • Willingness to learn and adapt quickly to new AI technologies.
  • Ability to work collaboratively in a team environment.
  • Attention to detail and focus on delivering quality work.
  • Good communication skills to work effectively with technical and non-technical stakeholders.


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