Requirements
- 8+ years of experience
- Hands-on experience in Machine Learning across both supervised and unsupervised techniques: Forecasting, Classification, Regression, Text Mining, NLP, Decision Trees, Adaptive Decision Algorithms, Random Forest, Search Algorithms, Gradient algorithms, etc.
- Exposure to pre-trained models, LLMs (Large Language Models), and GenAI technologies.
- Solid foundation in statistical techniques: ANOVA, Hypothesis Testing, Chi-Square tests.
- Experience managing ML model lifecycle end-to-end in production: from problem framing, data engineering, model development, training, deployment, and improvement of ML projects. MLOps, for monitoring and optimization.
- Have comprehensive experience in architecting, designing, and developing multiple ML production solutions. Min 5 successful AI/ML project deliveries with tangible business outcomes.
- Ability to analyze model performance and derive prescriptive ML or business actions from insights.
- Proficiency in Python and popular analytical libraries: Pandas, Scikit-learn, Seaborn, Matplotlib, NumPy, NLTK etc.
- Strong understanding of RDBMS technologies: MySQL, Oracle, MS SQL.
- Expert in NLP techniques.
- Experience working with AI cloud platforms (Google Cloud/ AWS/ Azure) is required.
- Familiarity with best practices for benchmarking, validation, and testing AI solutions for production.
- Expertise in optimizing AI/ML solutions for both accuracy and performance.
- Engage in pre-sales activities, including solutioning, scoping, estimation, and proposal development for AI/ML and GenAI projects.
- Providing consulting and advisory services to customer AI/ML
Nice to Have
- Practical knowledge of Neural Networks / Deep Learning frameworks like TensorFlow, Keras.
- Familiarity with HTML/CSS for creating simple web interfaces or dashboards.
- Expert in Azure and AWS AI Services. And open-source models, Hugging Face LLM
- AWS AI Services: AWS Bedrock, Amazon SageMaker, AWS Textract
- Azure AI Services: Azure AI Studio, Azure OpenAI, ML Studio, Cognitive Service, Azure Document Intelligence
- Possess deep knowledge in Text Embedding and Vector databases (AI Search, Pinecone, Weaviate, etc.)
