On-site
Part Time
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
Good to have skills : Python (Programming Language), React.js, Microsoft Azure Machine Learning
Minimum 7.5 year(s) of experience is required
Educational Qualification : BTECH
Summary We are looking for a highly skilled Principal Engineer to lead the design and implementation of advanced AI and deep learning solutions. This role requires deep expertise in Large Language Models (LLMs), cloud-based AI deployment on Azure, and full-stack software development using .NET and Python. You will drive the technical strategy, mentor engineering teams, and collaborate with product and data science teams to build scalable, high-performance AI systems that solve complex business challenges. Educational qualification: Bachelor’s or Master’s degree in Computer Science, Engineering, or related field. 10+ years of professional software engineering experience with at least 5 years focused on AI/ML development. Technical experience & Professional attributes: Strong experience working with Large Language Models (e.g., GPT, BERT) and deep learning frameworks (TensorFlow, PyTorch). Proficiency in Python and .NET (C#) for developing scalable AI solutions. Hands-on experience with Microsoft Azure AI services (Azure ML, Cognitive Services, AKS). Expertise in cloud-native architectures, microservices, and container orchestration. Proven track record of leading engineering teams and driving architecture decisions. Strong problem-solving skills and ability to deliver results in ambiguous, fast-paced environments. Excellent verbal and written communication skills. Must have skills: Experience with NLP libraries like Hugging Face Transformers, spaCy. Familiarity with MLOps practices and tooling (model training pipelines, monitoring, versioning). Knowledge of distributed systems and data engineering concepts. Experience implementing CI/CD pipelines and DevOps automation. Contributions to AI-related open-source projects or publications. Additional information: PhD or advanced research background in AI/ML or related fields. You will be working with a Trusted Tax Technology Leader, committed to delivering reliable and innovative solutions
Accenture
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