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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 : Machine Learning Operations
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 and cloud-based services. The role requires managing end-to-end application pipelines, ensuring solutions are production-ready and scalable. Daily activities may include integrating generative AI models, working with deep learning frameworks, and developing intelligent systems such as chatbots and image processing tools. Collaboration with cross-functional teams to align technical solutions with project goals is also a key aspect of the role, fostering innovation and continuous improvement in AI-driven products.
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 : Machine Learning Operations
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 and cloud-based services. The role requires managing end-to-end application pipelines, ensuring solutions are production-ready and scalable. Daily activities may include integrating generative AI models, working with deep learning frameworks, and developing intelligent systems such as chatbots and image processing tools. Collaboration with cross-functional teams to align technical solutions with project goals is also a key aspect of the role, fostering innovation and continuous improvement in AI-driven products.
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 optimize AI model deployment and maintenance.
- Assist in documenting technical processes and best practices to support knowledge sharing.
- Support junior team members by providing guidance and sharing expertise.
- Must To Have Skills: Proficiency in Machine Learning Operations.
- Experience with cloud platforms and AI service integration.
- Strong understanding of model deployment, monitoring, and lifecycle management.
- Familiarity with containerization and orchestration tools for scalable AI solutions.
- Ability to troubleshoot and optimize AI pipelines for performance and reliability.
- The candidate should have minimum 3 years of experience in Machine Learning Operations.
- This position is based at our Pune office.
- A 15 years full time education is required.
More Info
Key Skills
Orchestration tools
Monitoring and lifecycle management
Model deployment
Cloud platforms
Machine Learning Operations
AI service integration
About Company
Skills:
snowflake , Machine Learning, Pyspark, ELT, Nlp, MLops, Databricks, Python, Etl, AI Agents, LLMOps, Databricks Notebooks, RAG LangChain, Delta Lake, cloud data platforms, Databricks Workflows
Skills:
Python, Model Lifecycle Management, Model Deployment, ML Pipeline Development, Machine Learning Operations, Cloud AI services, Monitoring Optimization, Machine learning frameworks, Multi Cloud skills
Skills:
Python, Ml, Computer Vision, C, Tensorflow, Opencv, Linux, Pytorch, Cuda, Kubernetes, Docker, Git, ONNX, Ai, cloud platforms, Real-time video processing, TensorRT, RTSP video streaming