Artificial Intelligence Engineer
4 weeks ago
The impact that you will be making:
- Solve complex business problems of the global supply chain & retail industry through Machine Learning, especially leveraging Generative AI.
- Build cutting-edge GenAI solutions, leveraging both external assets (e.g., ChatGPT) as well as proprietary models, to efficiently address real-world problems.
- Play a critical role in developing/evolving industry-disrupting Foundational Model for Forecasting, and integrating the same into various product offerings.
- Deliver AI R&D objectives for one or more project modules, and work with other AI leads, AI architects, and CTO to design & develop new Deep Learning/GenAI architectures and algorithms.
- Contribute to the IP generation process in the company, and work towards patenting key inventions.
- Collaborate with various stakeholder groups to identify opportunities for applying GenAI to solve real-world problems.
What lands you in this role
- 4-6 years in Machine Learning with at least 2-3 years in the following areas:
- Deep Learning
- Generative AI
- Computer Vision or Natural Language Processing
- Strong conceptual knowledge of:
- Generative modeling techniques (e.g., Autoencoders, Diffusion & Transformer architectures)
- Efficient Fine-tuning mechanisms (e.g., Adapter training, Multi-task learning, etc.)
- Hyperparameter Optimization (especially Bayesian & Multi-fidelity Optimization techniques.)
- Strong understanding of the global GenAI ecosystem, and how it continues to evolve.
- Proficiency in Python, and associated frameworks like TensorFlow or PyTorch.
- Strong communication skills, including the ability to explain advanced technical concepts, ideas, and solutions to both technical and non-technical collaborators.
- Ability to work under minimal supervision and in a fast-paced environment.
- Candidates with prior experience in building or fine-tuning LLMs will be given preference.
- Candidates with Masters or Ph.D. in computing/systems, mathematics, machine learning or related areas will be preferred.
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