Machine Learning/ Generative AI Consultant

Infosys Consulting is a leading innovator in the tech industry, specializing in artificial intelligence and machine learning solutions. We work with a diverse range of clients to deliver cutting-edge AI technologies that drive business growth and innovation. We are looking for a talented Machine Learning/Generative AI Consultant to join our team and help us build the future of AI.

Key Responsibilities:

1. Collaborate with clients to understand their business needs and translate them into technical requirements.
2. Design, develop, and deploy machine learning and generative AI models, including NLP models, computer vision models, and reinforcement learning systems.
3. Conduct research and stay updated on the latest advancements in AI and machine learning technologies, particularly in generative models such as GANs, VAEs, and diffusion models.
4. Analyze large datasets to uncover patterns, insights, and opportunities for machine learning applications.
5. Optimize and fine-tune models for performance, scalability, and accuracy.
6. Build and maintain scalable data pipelines for model training and deployment.
7. Provide technical guidance and mentorship to junior data scientists and engineers.
8. Communicate complex technical concepts and results to non-technical stakeholders in a clear and concise manner.
9. Develop and present client deliverables, including project plans, progress reports, and final presentations.
10. Participate in client meetings and workshops to showcase AI capabilities and provide thought leadership on AI strategies.

Requirements:

1. Master\’s or Ph.D. in Computer Science, Data Science, Machine Learning, or a related field.
2. Proven experience (3+ years) in machine learning and generative AI, with a strong portfolio of projects involving models like GANs, VAEs, transformers, or diffusion models.
3. Proficiency in programming languages such as Python, R, or Julia, and experience with ML frameworks like TensorFlow, PyTorch, or Keras.
4. Strong understanding of deep learning architectures, neural networks, and statistical modeling techniques.
5. Experience with cloud platforms (AWS, Azure, Google Cloud) and MLOps tools for model deployment and management.
6. Excellent problem-solving skills with a strong ability to identify and troubleshoot issues in model performance and data quality.
7. Effective communication and presentation skills, with the ability to convey complex concepts to both technical and non-technical audiences.
8. Ability to work independently as well as collaboratively in a team environment.

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