Cloud Suite Administrator

Experience: A minimum 2-3 years of hands-on experience in implementing AI/ML models in enterprise systems.

AI/ML Concepts: In-depth understanding of supervised and unsupervised learning, reinforcement learning, deep learning, and probabilistic models.

Programming Languages: Proficiency in Python or R, along with querying languages like SQL.

Data Handling: Ability to work with large datasets, perform data preprocessing, and wrangle data effectively.

Cloud Infrastructure: Experience with AWS Services and ML services for implementing ML solutions is highly preferred.

Frameworks and Libraries: Familiarity with scikit-learn, Keras, TensorFlow, PyTorch, or NLTK is a plus.

Analytical Skills: Strong critical thinking abilities to identify problems, formulate hypotheses, and design experiments.

Business Process Understanding: Good understanding of business processes and how they can be automated

Domain Expertise: Familiarity with Demand Forecasting, Anomaly Detection, Pricing, Recommendation, or Analytics solutions.

Global Project Experience: Proven track record of working with global customers on multiple projects.

Customer Interaction: Experience facing customers and understanding their needs.

Communication Skills: Excellent verbal and written communication skills.

Analytical Mindset: Strong analytical and problem-solving skills.

Collaboration: Ability to work independently and collaboratively.

Educational Background: Bachelor s or master s degree in computer science, Mathematics, Statistics, or a related field.

Specialization: Coursework or specialization in AI, ML, Statistics & Probability, Deep Learning, Computer Vision, or NLP/NLU is advantageous.

Data Analysis and Interpretation: Conduct in-depth analysis of historical data and trends to identify patterns, correlations, and anomalies that can inform future business strategies.

Documentation and Communication: Program and write maintainable and well-documented code and write summaries and reports to present technical findings/conclusions and project status updates.

Intelligent, fast-thinking and highly motivated with a strong problem-solving and analytical skills.

Experience with prompt engineering techniques, LLM finetuning and familiarity with LLM-based workflows/architectures such as retrieval-augmented generation.

Experience with Python (NumPy, Pandas, etc) must have experience in at least one of the common LLM toolkits, etc. ,

SQL for databases querying.

Clear knowledge of a variety of machine learning techniques (especially for time series forecasting) and of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, etc. ) is a huge plus.

Excellent presentation, written, and verbal communication skills for coordinating across teams.

Be able to work independently and as part of a team with 24/7 Support Operations.