Lead AI Engineer

Position

Experience Required

Company

Work Location:

Notice Period:

Role Overview

Senior AI Engineer

Key Responsibilities:

• AI Model Development

  : Design, train, and deploy AI models for diverse use cases, including:

• Computer Vision

  : Image recognition, object detection, segmentation etc.

• Natural Language Processing (NLP)

  : Text classification, summarization, question-answering systems etc.

• Generative AI

  : Fine-tuning and deploying

  open-source large language models (LLMs)

  and Private Models.

• RAG (Retrieval-Augmented Generation)

  : Implement AI systems combining retrieval with generative models.
• Optimize AI models for performance, scalability, and accuracy using core algorithms (regression, KNN, SVM, etc.).

• Open-Source LLM Development

  :
• Develop and fine-tune

  open-source LLMs

  to cater to domain-specific needs.
• Deploy open-source LLMs effectively in production environments, ensuring scalability and low latency.
• Explore and implement open-source tools and frameworks like Hugging Face, LangChain, and Transformer libraries.

• Integration & Architecture

  :
• Integrate AI solutions with

  Vector/Graph db

  for advanced data relationships and queries.
• Implement and manage

  MLOps

  /

  LLMOps pipelines

  for efficient deployment, monitoring, and scaling of AI models.

• Leadership

  :
• Mentor and guide junior engineers, fostering innovation and skill development.
• Collaborate with cross-functional teams, including product management, data engineering, and software development, to align AI strategies with business goals.

• Infrastructure

  :
• Leverage cloud AI platforms (AWS SageMaker, Google Vertex AI, Azure AI) for scalable solutions.
• Adopt open-source frameworks and tools (e.g., TensorFlow, PyTorch, Hugging Face) for experimentation and development.

• Best Practices

  :
• Establish robust practices for coding, testing, and documenting AI solutions.
• Stay at the forefront of AI research and emerging trends like AGENTIC AI, RAG, and open-source LLM development.

Requirements:

Experience

• 5+ years of experience in AI/ML
• Proven expertise in designing and deploying AI solutions in production environments.

Technical Skills

• Strong proficiency in machine learning frameworks (TensorFlow, PyTorch, Scikit-learn).
• Hands-on experience with tools like Hugging Face, OpenAI API, and Google AI tools.
• In-depth understanding of

  core ML algorithms

  (regression, KNN, clustering, etc.) and

  deep learning models

  .
• Familiarity with

  open-source LLM development and deployment

• Experience with

  RAG architectures

  ,

  Graph Databases

  , and

  LLMOps

  practices.
• Expertise in CI/CD pipelines, containerization (Docker, Kubernetes), and cloud AI platforms (AWS, Google Cloud, Azure).

Domain Knowledge

• Familiarity with EdTech standards (LTI, xAPI, QTI) and adaptive learning systems is a strong plus.

Soft Skills

• Exceptional leadership and team mentoring abilities.
• Strong problem-solving skills and excellent communication for technical and non-technical stakeholders.

Education

• Bachelors or Masters degree in Computer Science, AI, Data Science, or related fields.

Why Join Us:

• Opportunity to lead AI initiatives that shape the future of education technology.
• Work in a collaborative, mission-driven environment with a focus on innovation.
• Engage with impactful projects and cutting-edge AI technologies.
• Competitive salary, benefits, and opportunities for professional growth.