Lead Engineer AI

Academian India

4 - 8 years

12 - 16 Lacs

pune

Posted:1 day ago| Platform:

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Skills Required

computer science lms data modeling coding machine learning cms open source monitoring sql python

Work Mode

Work from Office

Job Type

Full Time

Job Description

Key Responsibilities

AI Model Development:
Design, train, and deploy AI models for diverse use cases in
Computer Vision, NLP, and Generative AI
.
Fine-tune and deploy open-source large language models (LLMs) and private models for EdTech applications.
Implement
RAG (Retrieval-Augmented Generation)
systems combining retrieval with generative models.
Leverage
LangGraph
and
LangChain
for orchestration, multi-step workflows, and stateful agent design.
Data Engineering Integration:
Develop and integrate
real-time data pipelines
and event-driven architectures using
Kafka, Spark, or PySpark
.
Build secure, scalable, and cloud-native AI solutions using
AWS Bedrock, SageMaker, Google Vertex AI, Azure ML (AML), Azure AKS
, and related services.
Implement
MLOps/LLMOps pipelines
for efficient deployment, monitoring, and scaling of AI models.
AI Infrastructure Tools:
Work with modern AI toolkits and frameworks such as
Hugging Face Transformers, MLflow, and Databricks
.
Develop prompt engineering strategies and optimize LLMs for improved accuracy and relevance.
Contribute to internal AI frameworks and toolkits for accelerated adoption across teams.
Leadership:
Mentor and guide junior engineers, fostering innovation and skill development.
Collaborate with cross-functional teams to align AI strategies with business goals.
Promote best practices in coding, testing, documentation, and model lifecycle management.

Requirements

Experience:
5+ years in AI/ML system development and deployment in production environments.
2+ years of experience in team leading.
Proven track record of designing AI systems in
cloud environments
and working with
data-intensive pipelines
.
Technical Skills:
Strong Python proficiency (async programming, multi-step workflows).
Expertise in machine learning and deep learning frameworks:
TensorFlow, PyTorch, Scikit-learn
.
Proficiency with tools like
Hugging Face, LangChain, LangGraph, OpenAI API, and Bedrock API
.
Hands-on experience with
ETL/ELT workflows
, data transformations, and
SQL (data modeling, normalization, optimization)
.
Knowledge of
RAG architectures, Graph Databases, and MCP (Model Context Protocol)
.
Familiarity with
CI/CD pipelines
, containerization (
Docker, Kubernetes
), and cloud AI platforms (
AWS, GCP, Azure
).
Domain Knowledge:
Understanding of
EdTech standards
like
LTI, xAPI, QTI
, and SCORM.
Familiarity with
adaptive learning systems
and educational content pipelines.
Knowledge of workflows in K-12, higher education, and corporate learning environments 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:
Bachelor s or master s degree in computer science, AI, Data Science, or related fields.

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