AI LEAD @ Zensar

Collaborate with clients to understand their business needs and identify opportunities for AI-driven solutions.
Design and develop PoCs using AI and machine learning technologies to demonstrate the feasibility and value of proposed solutions.
Work closely with client, cross-functional teams, including data scientists, engineers, and product managers, to ensure successful implementation of PoCs.
Stay up-to-date with the latest advancements in AI and related technologies, and apply this knowledge to improve our solutions.
Present PoCs to clients, gather feedback, and iterate on solutions to meet client requirements.
Provide technical guidance and mentorship to junior team members.

Requirements:
Proven experience in designing and developing AI solutions, including PoCs.
Strong knowledge of machine learning algorithms, data processing, and model deployment.
Proficiency in programming languages such as Python, R, or Java.
Experience with AI frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn.
Excellent problem-solving skills and the ability to think creatively.
Strong communication and presentation skills, with the ability to explain complex concepts to non-technical stakeholders.
Ability to work independently and as part of a team in a fast-paced environment.

Preferred Qualifications:
Experience with cloud platforms such as AWS, Azure, or Google Cloud.
Knowledge of natural language processing (NLP) and computer vision techniques.
Familiarity with agile development methodologies.

Technical Stack:
Programming Languages: Python, R, Java
AI Frameworks/Libraries: TensorFlow, PyTorch, scikit-learn
Data Processing: Pandas, NumPy
Model Deployment: Docker, Kubernetes
Cloud Platforms: AWS, Azure, Google Cloud
Version Control: Git, GitHub, GitLab
CI/CD Tools: Jenkins, Travis CI

Experience Needed:
Minimum of 3-5 years of experience in AI and machine learning.
Hands-on experience in developing and deploying machine learning models.
Experience in building and presenting PoCs to clients.
Familiarity with data preprocessing, feature engineering, and model evaluation techniques.
Experience in working with large datasets and distributed computing.