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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 : Large Language Models (LLMs)
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 AI models and exploring various AI domains such as deep learning, neural networks, conversational agents, and image analysis. Collaboration with cross-functional teams to align AI capabilities with project goals and continuous refinement of AI-driven solutions are key aspects of the daily routine.
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 : Large Language Models (LLMs)
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 AI models and exploring various AI domains such as deep learning, neural networks, conversational agents, and image analysis. Collaboration with cross-functional teams to align AI capabilities with project goals and continuous refinement of AI-driven solutions are key aspects of the daily routine.
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 enhance AI model performance and deployment strategies.
- Assist junior team members by sharing knowledge and providing guidance on AI implementation challenges.
- Continuously monitor and optimize AI applications to maintain high quality and efficiency.
- Must To Have Skills: Proficiency in Large Language Models (LLMs).
- Experience with designing and deploying AI applications using cloud AI services and on-premises infrastructure.
- Strong understanding of generative AI models and their practical applications.
- Familiarity with deep learning frameworks and neural network architectures.
- Ability to develop and maintain production-ready AI pipelines ensuring robustness and scalability.
- Knowledge of chatbot development and image processing techniques.
- The candidate should have minimum 3 years of experience in Large Language Models (LLMs).
- This position is based at our DDC2A - SEZ location.
- A 15 years full time education is required.
More Info
Job Type:
Industry:
Employment Type:
Key Skills
Neural network architectures
On-premises infrastructure
Deep learning frameworks
Cloud AI services
Generative AI models
Chatbot development
Production-ready AI pipelines
Large Language Models (LLMs)
About Company
Skills:
data engineering , Neural Networks, large-scale data processing frameworks and tools, data pipeline development and management in cloud and on-premise environments, AI-driven image processing, generative AI models, deep learning architectures, AI model integration and deployment techniques
Skills:
Large Language Models (LLMs), Tensorflow, Pytorch, Python, Computer Vision, Generative AI, Hugging Face ecosystem, RAG systems, Prompt Engineering, Agentic AI, Deploying optimized models in cloud and/or edge environments, NLP techniques
Skills:
Tensorflow, Natural Language Processing, Generative Adversarial Networks, Python, Pytorch, Machine Learning Algorithms, Text-to-Image, Conditional GANs, Latent Diffusion, Draping algorithms, Deep Neural Networks, InPainting, Image-to-Image, Feature engineering, Speech-to-Text, Data pre-processing, Text-to-Speech, Stable Diffusion, Texture Mapping, Fabric simulation, Transformers
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
Skills:
Numpy, Git, Pandas, Databricks, Python, Sql, scikit-learn, AWS SageMaker, Vector databases, Similarity search concepts, NoSQL databases, Jupyter, Generative AI models