Job Title: EA - Information Technology - Intern - Mumbai
Your potential, unleashed.
India’s impact on the global economy has increased at an exponential rate and Deloitte presents an opportunity to unleash and realize your potential amongst cutting edge leaders, and organisations shaping the future of the region, and indeed, the world beyond.
At Deloitte, your whole self to work, every day. Combine that with our drive to propel with purpose and you have the perfect playground to collaborate, innovate, grow, and make an impact that matters.
The team
The Enabling Areas – Information Technology team is responsible for building & maintaining different applications for Deloitte South Asia that focuses on providing employee experience.
Role Overview:
As a Machine Learning Engineer - Design, implement, and deploy state-of-the-art generative models and machine learning algorithms.
Key Responsibilities:
Model Development: Design, develop and deploy generative models such as GANs (Generative Adversarial Networks), transformers, and large language models.
Research & Innovation: Stay on top of the latest trends in AI, including research papers, open-source advancements, and breakthroughs in generative models and deep learning. Contribute to the development of proprietary algorithms and techniques.
Data Preparation & Preprocessing: Collaborate with data engineers to prepare, clean, and process large datasets suitable for training generative models.
Training & Optimization: Train large-scale models using advanced machine learning techniques. Optimize models for efficiency, scalability, and performance in real-world applications.
Deployment & Monitoring: Deploy models into production environments, and set up monitoring and testing to ensure model accuracy, performance, and robustness over time.
Collaboration: Work closely with cross-functional teams, including software engineers, data scientists, and product managers, to integrate AI/ML solutions into our products and services.
Code Quality & Documentation: Write clean, efficient, and maintainable code. Document processes, algorithms, and model decisions to ensure transparency and ease of collaboration.
Continuous Improvement: Analyze model performance, identify areas for improvement, and iteratively refine models based on performance metrics and real-world feedback.
Qualifications:
Education: Bachelor's, Master’s, or PhD in Computer Science, Mathematics, Data Science, Engineering, or a related field.
Experience:
Proven experience in fine-tuning models like GANs, VAEs, Transformers, or other generative architectures.
Strong programming skills in Python (preferred).
Familiarity with machine learning libraries and frameworks like TensorFlow, PyTorch, Hugging Face and Keras.
Skills & Knowledge:
Experience in fine-tuning pre-trained models (e.g., GPT-3, BERT, etc.).
Strong understanding of deep learning algorithms, architectures, and optimization techniques.
Hands-on experience with large-scale model training, GPU computing, and cloud platforms like Azure.
Familiarity with NLP, computer vision, or other relevant fields of generative AI.
Understanding of model interpretability, explainability, and ethical AI considerations.
Experience in fine-tuning pre-trained models (e.g., GPT-3, BERT, etc.).
Good To Have
Familiarity with MLOps practices, version control (Git), and CI/CD pipelines.
Contribution to open-source AI projects or published research papers in AI/ML.
How you’ll grow
Connect for impact
Our exceptional team of professionals across the globe are solving some of the world’s most complex business problems, as well as directly supporting our communities, the planet, and each other. Know more in our Global Impact Report and our India Impact Report.
Empower to lead
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Drive your career
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Everyone’s welcome… entrust your happiness to us
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