Generative AI Engineer – Data ...

Best Course News; Bengaluru; On-site; INR 600,000 - 1,000,000; Full time

Job summary

A leading financial services company is seeking a Generative AI Engineer – Data & Analytics to drive insights through advanced analytics and AI solutions. The ideal candidate will have hands-on experience in ML and analytics, with over a year in the field. You will work with large datasets and collaborate cross-functionally to influence business strategies. Responsibilities include building and fine-tuning ML models, delivering strategic insights to leadership, and deploying compliant AI solutions.

Qualifications

• Minimum 1+ years of experience in the analytics / AI / ML domain.
• Strong logical reasoning, problem solving, and numerical aptitude.
• Hands-on experience with large datasets and big data technologies.

Responsibilities

• Deliver actionable insights and strategic recommendations.
• Scale advanced analytics across business functions.
• Build and deploy scalable AI/ML systems.

Skills

Strong analytical skills

Experience with ML algorithms

Hands-on expertise with Python

Proficiency in CI/CD

Education

M.Tech / B.E. / B.Tech / M.Sc. in a related field

Tools

Docker

Kubernetes

LangChain

Job description

#### Generative AI Engineer – Data & Analytics##### TVS Credit Services Ltd* Bengaluru#### DescriptionJob descriptionThe role aims to instill a culture of data aggregation, advanced analytics, and AI-driven insights across the organization. The incumbent will identify patterns in data to improve consumer experience, enhance decision-making, and contribute towards achieving organizational goals and objectives.Key ResponsibilitiesFunctionalScale analytics capability across business functions and guide the organizations data strategy.Organize, process, and analyze large, diverse datasets across multiple platforms.Identify and communicate key insights to influence product and business strategy.Collaborate with vendors and partners in a technical capacity on scope, approach, and deliverables.Develop proofs of concept to validate ideas and solutions.Partner with business teams to formalize analytical requirements and design robust, efficient, and reliable reporting solutions.Design and implement advanced statistical testing and models for problem solving.Deliver clear and concise insights to senior leadership, elevating analytics into strategic recommendations.AI/ML & LLM-SpecificBuild, train, and fine-tune data pipelines for ML and LLM use cases (dataset creation, cleaning, augmentation, labeling workflows).Apply expertise in ML algorithms (e.g., XGBoost, SVM) and statistical modeling techniques (regression, segmentation, forecasting, hypothesis testing, A/B testing, decision trees, etc.).Work hands-on with modern LLMs and embeddings (OpenAI, Anthropic, LLaMA-family, Mistral, etc.).Implement instruction tuning/fine-tuning methods (LoRA, PEFT, adapters).Integrate AI models with backend and frontend systems using APIs, batching, caching, and streaming responses.Develop safe, secure, and compliant AI applications, including safety layers (prompt injection defense, hallucination reduction, PII redaction).Build and deploy scalable AI/ML systems using MLOps practices (Docker, Kubernetes, CI/CD).Work with frameworks and tools such as LangChain, Hugging Face Transformers, Ray/Serve, and vector databases (FAISS, Pinecone, Milvus).Job RequirementsQualificationsM.Tech / B.E. / B.Tech / M.Sc. in Computer Science, Statistics, Mathematics, Operational Research, Econometrics, or a related quantitative field.ExperienceMinimum 1+ years of experience in the analytics / AI / ML domain.Prior exposure to BFSI/NBFC industry is desirable.Functional CompetenciesStrong analytical, logical reasoning, problem solving, and numerical aptitudeProven experience with large datasets and big data technologies (SQL, Hadoop, Hive).Advanced knowledge of data mining, statistical analysis, and ML algorithms.Hands-on expertise with Python for analytics and AI development.Proficiency in CI/CD, MLOps, and modern AI/ML engineering practices.Familiarity with Azure OpenAI, LangChain, Hugging Face, and related ecosystems.Knowledge of speech-to-text systems (e.g., Whisper, Indian languages a plus).Desirable SkillsExperience in BFSI/NBFC domain.Exposure to speech-to-text and multilingual NLP solutions.#### Role and Responsibilities* Key Responsibilities Analytics & Business Impact Scale advanced analytics and AI capabilities across multiple business functions. Identify trends, patterns, and insights from large, complex datasets to influence product and business strategies. Deliver clear, actionable insights and strategic recommendations to senior leadership. Partner with business teams to translate requirements into robust analytical and reporting solutions. Develop proof-of-concept (PoC) solutions to validate AI and analytics use cases. AI / ML & Generative AI Engineering Build, train, and fine-tune data pipelines for ML and LLM-based use cases, including data preparation, augmentation, labeling, and validation. Design and implement machine learning models using techniques such as regression, classification, segmentation, forecasting, hypothesis testing, A/B testing, and decision trees. Apply ML algorithms such as XGBoost, SVM, and ensemble models for business problem-solving. Work hands-on with modern Large Language Models (LLMs) and embeddings (OpenAI, Anthropic, LLaMA-family, Mistral, etc.). Implement instruction tuning and fine-tuning techniques such as LoRA, PEFT, and adapters. AI Application Development & Deployment Integrate AI models with backend and frontend systems using APIs, batching, caching, and streaming responses. Build safe, secure, and compliant AI solutions with safeguards for prompt injection, hallucination reduction, and PII protection. Design and deploy scalable AI/ML systems using MLOps best practices (Docker, Kubernetes, CI/CD pipelines). Utilize modern AI frameworks and tools such as LangChain, Hugging Face Transformers, Ray/Serve, and vector databases (FAISS, Pinecone, Milvus). Collaboration & Vendor Management Collaborate with vendors and external partners on technical scope, architecture, and deliverables. Work cross-functionally with product, engineering, risk, and business teams to ensure AI solutions align with organizational goals.| Designation | : | Generative AI Engineer – Data & Analytics || Work experience | : | 0 - 1 |### Skills: