Junior AI Engineer

Bengaluru - India

Monthly Salary: Not Disclosed

Posted on: 9 hours ago

Vacancies: 1 Vacancy

Job Summary

Job title: Junior AI Engineer JD

AI Engineer
A Senior AI Engineer leads the design development and implementation of artificial intelligence solutions
that address specific business problems. Individuals in this role have extensive experience with machine
learning models natural language processing computer vision or other AI technologies. They
collaborate closely with data scientists data engineers and cloud engineers to deliver AI solutions that
drive business value. Key Tasks & Responsibilities
AI Solution Development
Design and develop machine learning models algorithms and AI systems.
Implement and optimize AI models for performance and scalability.
Data Management and Preprocessing
Collect preprocess and analyze large datasets to build effective AI models.
Ensure data quality and integrity through rigorous data validation processes.
Model Training and Evaluation
Train test and validate AI models to ensure accuracy and reliability.
Perform model evaluation and tuning to improve performance metrics.
Integration and Deployment
Integrate AI models into existing systems and applications.
Deploy AI solutions into production environments and monitor their performance.
Collaboration and Communication
Work closely with data scientists software engineers and business stakeholders to
understand requirements and deliver solutions.
Communicate complex AI concepts and results to non-technical stakeholders.
Research and Innovation
Stay updated with the latest AI trends technologies and best practices.
Conduct research to explore new AI methodologies and applications.
Documentation and Reporting
Document AI models processes and workflows.
Prepare reports and presentations on AI project status results and impacts. Qualifications & Competencies
Required:
1) Educational Background
a) Bachelors degree in Computer Science Data Science or a related field is required. A Masters
degree is a plus.
2) Experience
a) 2 years of experience in AI roles with the required skills.
3) Deep Learning & Transformer Architecture
a) Basic understanding of neural networks and their applications.
b) Familiarity with transformer architecture and its use cases.
c) Exposure to multi-modal diffusion architectures is a good-to-have.

4) LLM Development & Implementation
a) Hands-on experience in building and fine-tuning large language models (LLMs) for various
applications including:
b) Document comparison and chunking.
c) Retrieval-Augmented Generation (RAG).
d) Chatbot and NLP-based applications.
e) Experience with embedding models and vector database integration (e.g. FAISS Pinecone
AWS OpenSearch).
5) Multi-Agent & Rules-Based AI Implementation
a) Ability to implement rules-based AI logic in applications.
b) Experience in developing multi-agent AI systems with orchestration.

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c) Familiarity with tools like LangChain LangGraph and LlamaIndex (GPT Index) for chaining
multiple LLM workflows.
6) AI Tools & Libraries
a) Strong knowledge of AWS AI services such as Amazon Bedrock and SageMaker.
b) Hands-on experience with Hugging Face OpenAI API and GPT models.
7) Cloud & DevOps (AWS Focused)
a) Experience in deploying AI models using AWS services like Fargate EKS and ECS.
b) Familiarity with implementing CI/CD pipelines for AI models using AWS CodeBuild CodePipeline
and Lambda Functions.
c) Basic experience with containerized AI services using Docker and Kubernetes.
8) Model Deployment & API Integration
a) Hands-on Python experience with at least one AI project delivered from inception to production.
b) Experience in API development and integration including REST APIs GraphQL and AWS API
Gateway.
c) Ability to reuse and customize GitHub-based AI repositories for production use.
9) Preferred Qualifications:
a) Relevant certifications in AI machine learning or data science (e.g. AWS Certified Cloud
Practitioner Azure Fundamentals).
b) Experience with multi-modal architectures and advanced AI techniques.
c) Understanding of AI ethics and governance practices.
d) Familiarity with Agile methodologies and project management tools.

Job title: Junior AI Engineer JD AI Engineer A Senior AI Engineer leads the design development and implementation of artificial intelligence solutions that address specific business problems. Individuals in this role have extensive experience with machine learning models natural language processing ...

Job title: Junior AI Engineer JD