B. Tech or BE (4 years bachelor degree)

Senior Principal Analyst – Data Science (Gen AI)

Key Responsibilities:

• Apply software and AI engineering patterns and principles to design, develop, test, integrate, maintain and
troubleshoot complex and varied Generative AI software solutions and incorporate security practices in newly
developed and maintained applications.
• Collaborate with cross-functional teams to define AI project requirements and objectives, ensuring alignment
with overall business goals.
• Conduct research to stay up to date with the latest advancements in generative AI, machine learning, and deep
learning techniques and identify opportunities to integrate them into our products and services, optimizing
existing generative AI models and RAG for improved performance, scalability, and efficiency, developing and
maintaining pipelines and RAG solutions including data preprocessing, prompt engineering, benchmarking and
fine-tuning.
• Develop clear and concise documentation, including technical specifications, user guides and presentations, to
communicate complex AI concepts to both technical and non-technical stakeholders.
• Independently handle complex issues with minimal supervision, while escalating only the most complex issues
to appropriate staff

Qualifications:
• Bachelor’s degree (B. Tech/B.E.) or master’s degree (M. Tech/M.E.) in Computer Science, Information
Technology, or a related field.
• Minimum of 8 years of related AI/ML work experience
• You are proficient in Python and have experience with machine learning libraries and frameworks. Proficient in
Python, TensorFlow, PyTorch, and other relevant AI/ML libraries and frameworks.

• NLP & LLM Expertise: Strong experience (4+) specifically with NLP applications and LLMs (such as GPT, BERT,
etc.), including model training, fine-tuning, and deploying at scale.
• Cloud: Hands-on experience with cloud services (AWS, GCP, or Azure) for AI/ML deployment.
• Have a deep understanding of industry leading Foundation Model capabilities and its application.
• 2+ years of experience with implementing information search and retrieval at scale (RAG applications),
using a range of solutions ranging from keyword search to semantic search using embeddings.
• You are familiar with cloud-based Generative AI platforms and services
• Full stack software engineering experience to build products using Foundation Models
• Confirmed experience architecting applications, databases, services or integrations

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Senior Principal Analyst-AI Engineering

Responsibilities

We are seeking a highly skilled and motivated Senior Principal Analyst to join our team. The ideal candidate will
possess a strong technical background with expertise in various programming languages and data technologies,
Data Science and Artificial Intelligence coupled with exceptional business acumen and communication skills. As a
Senior Principal Analyst, you will be responsible for leadingtechnical initiatives, designing innovative solutions, and
providing expert consultation to our clients.

Key Responsibilities:
• Develop and implement machine learning models (classification, regression) using advanced techniques.
• Select features, build, and optimize classifiers and regressors using traditional ML methods such as decision
trees, random forests, and gradient boosting.
• Perform data pre-processing, including data cleaning and transformation for analysis.
• Leverage statistical methods to analyze datasets, perform hypothesis testing, and implement predictive models.
• Lead end-to-end model development lifecycle: from data wrangling to deployment.
• Mentor junior data scientists and guide them in the application of machine learning algorithms.
• Collaborate with business stakeholders to translate their needs into actionable data-driven solutions.
Technical Skills:
• Advanced proficiency in Python and libraries such as scikit-learn and XGBoost.
• Strong understanding of ML algorithms (SVM, KNN, Naive Bayes) and statistical techniques (regression,
clustering, time-series analysis).
• Expertise in model validation and evaluation techniques (cross-validation, confusion matrix, AUC-ROC).
• Experience with data visualization tools (Tableau, Power BI) and SQL for data extraction.
• Familiarity with cloud environments (AWS, GCP).
Qualifications:
• Bachelor’s or master’s degree in computer science, statistics, or related fields.
• 8+ years of experience in building and deploying traditional machine learning models.

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