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:
- Collaborate with clients to understand their business needs and translate them into technical requirements.
- Design, develop, and deploy machine learning and generative AI models, including NLP models, computer vision models, and reinforcement learning systems.
- 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.
- Analyze large datasets to uncover patterns, insights, and opportunities for machine learning applications.
- Optimize and fine-tune models for performance, scalability, and accuracy.
- Build and maintain scalable data pipelines for model training and deployment.
- Provide technical guidance and mentorship to junior data scientists and engineers.
- Communicate complex technical concepts and results to non-technical stakeholders in a clear and concise manner.
- Develop and present client deliverables, including project plans, progress reports, and final presentations.
- Participate in client meetings and workshops to showcase AI capabilities and provide thought leadership on AI strategies.
Requirements:
- Master's or Ph.D. in Computer Science, Data Science, Machine Learning, or a related field.
- 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.
- Proficiency in programming languages such as Python, R, or Julia, and experience with ML frameworks like TensorFlow, PyTorch, or Keras.
- Strong understanding of deep learning architectures, neural networks, and statistical modeling techniques.
- Experience with cloud platforms (AWS, Azure, Google Cloud) and MLOps tools for model deployment and management.
- Excellent problem-solving skills with a strong ability to identify and troubleshoot issues in model performance and data quality.
- Effective communication and presentation skills, with the ability to convey complex concepts to both technical and non-technical audiences.
- Ability to work independently as well as collaboratively in a team environment.