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AI / ML Engineer
Job Description
Project Role : AI / ML Engineer
Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing.
Must have skills : Generative AI
Good to have skills : NA
Minimum 3 Year(s) Of Experience Is Required
Educational Qualification : 15 years full time education
Summary
As an AI / ML Engineer, a typical day involves designing and building advanced applications and systems that leverage artificial intelligence technologies. This role requires integrating cloud-based or on-premises pipelines to ensure solutions are production-ready and scalable. The work often includes applying generative artificial intelligence models to solve complex problems, as well as exploring areas such as deep learning, neural networks, conversational agents, and image analysis. Collaboration with cross-functional teams to refine and enhance AI-driven solutions is a key part of daily activities, ensuring innovative and efficient outcomes.
Roles & Responsibilities
Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing.
Must have skills : Generative AI
Good to have skills : NA
Minimum 3 Year(s) Of Experience Is Required
Educational Qualification : 15 years full time education
Summary
As an AI / ML Engineer, a typical day involves designing and building advanced applications and systems that leverage artificial intelligence technologies. This role requires integrating cloud-based or on-premises pipelines to ensure solutions are production-ready and scalable. The work often includes applying generative artificial intelligence models to solve complex problems, as well as exploring areas such as deep learning, neural networks, conversational agents, and image analysis. Collaboration with cross-functional teams to refine and enhance AI-driven solutions is a key part of daily activities, ensuring innovative and efficient outcomes.
Roles & Responsibilities
- Expected to perform independently and become an SME.
- Required active participation/contribution in team discussions.
- Contribute in providing solutions to work related problems.
- Collaborate with team members to continuously improve AI models and system performance.
- Document technical designs and implementation details to support knowledge sharing and maintenance.
- Assist junior team members by providing guidance and support in understanding AI concepts and project requirements.
- Must To Have Skills: Proficiency in Generative AI.
- Experience with designing and deploying AI models in cloud or on-premises environments.
- Strong understanding of deep learning architectures and neural network frameworks.
- Familiarity with building and optimizing conversational AI systems such as chatbots.
- Knowledge of image processing techniques and their application in AI solutions.
- The candidate should have minimum 3 years of experience in Generative AI.
- This position is based at our DDC5E - SEZ location.
- A 15 years full time education is required.
More Info
Job Type:
Industry:
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Key Skills
Neural network frameworks
Generative AI
Conversational AI systems
Deep learning architectures
Image processing techniques
Chatbots
About Company
Skills:
Large Language Models (LLMs), Image Processing, Neural network architectures, Generative AI, Agentic AI, On-premises infrastructure, Deep learning frameworks, Production-grade AI pipelines, Cloud AI services, Chatbot development
Skills:
Python Programming, Generative AI, RAG and embeddings, Prompt Engineering
Skills:
Machine Learning, Nlp, Docker, Python, AWS, Databases, Sql, Deep Learning, Gcp, Rest Apis, Azure, RAG agentic AI, vector search, embeddings, pgvector, Qdrant, vector databases, Pinecone, CI CD, model evaluation, backend systems, retrieval, experimentation, AI APIs, Generative AI, LLMs, scalable application architecture, Monitoring, prompt engineering, performance optimization, Milvus, Weaviate, production engineering practices
Skills:
Tensorflow, Pytorch, Gcp, MLops, Docker, Azure, Kubernetes, Python, AWS, LangChain, Generative AI, LLaMA, Scikit-learn, Pinecone, GPT, FAISS, LoRA, Weaviate, QLoRA, LlamaIndex, Large Language Models