Elevate Your Impact Through Innovation and Learning:
Evalueserve is a global leader in delivering innovative and sustainable solutions to a diverse range of clients, including over 30% of Fortune 500 companies. With a presence in more than 45 countries across five continents, we excel in leveraging state-of-the-art technology, artificial intelligence, and unparalleled subject matter expertise to elevate our clients' business impact and strategic decision-making. Our team of over 4,500 talented professionals operates in countries such as India, China, Chile, Romania, the US, and Canada. Our global network also extends to emerging markets like Colombia, the Middle East, and the rest of Asia-Pacific. Recognized by Great Place to Work® in India, Chile, Romania, the US, and the UK in 2022, we offer a dynamic, growth-oriented, and meritocracy-based culture that prioritizes continuous learning and skill development, work-life balance, and equal opportunity for all.
About Data Analytics (DA):
Data Analytics is one of the highest growth practices within Evalueserve, providing you rewarding career opportunities. Established in 2014, the global DA team extends beyond 1000+ (and growing) data science professionals across data engineering, business intelligence, digital marketing, advanced analytics, technology, and product engineering. Our more tenured teammates, some of whom have been with Evalueserve since it started more than 20 years ago, have enjoyed leadership opportunities in different regions of the world across our seven business lines.
What you will be doing at Evalueserve:
Model Development: Design, implement, and optimize generative models locally (on-premises) as well as Cloud platform, including:
- Retrieval-Augmented Generation (RAG) – Structured and Unstructured data.
- Agentic AI systems.
- LLMs and Multimodal LLMs like LLaMA, Mistral, Gemma, GPT etc, and their variants.
- Generative Adversarial Networks (GANs).
- Variational Autoencoders (VAEs).
- Diffusion Models, Reasoning Models.
- Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) Networks.
- Conditional Generative Models.
Collaboration: Work closely with product managers, data scientists, and software engineers to define project requirements and deliver effective solutions.
Data Handling: Gather, process, analyze large datasets training for generative models.
Research: Stay updated with the latest advancements in generative AI and related fields to enhance methodologies and technologies.
Performance Tuning: Optimize models for performance and scalability, ensuring they meet production standards.
Documentation: Maintain comprehensive documentation of processes, models, and experiments to facilitate knowledge sharing within the team.
Mentorship: Provide guidance to junior team members, fostering a collaborative and learning-oriented environment.
What we're looking for:
- We are looking for 6-8 years experienced Generative AI Engineer to join our innovative team. In this role, you will develop and implement generative AI models, including Retrieval-Augmented Generation (RAG) and Agentic AI systems to be developed and deployed on-premises locally on client network and Cloud platform, to enhance our products and services. Your expertise will help us leverage cutting-edge technologies to drive business success and improve user experiences.
Technical Requirements:
Programming Languages: Proficiency in Python for model development and data manipulation.
Frameworks and Libraries: TensorFlow, PyTorch, Keras, Langchain, Langgraph, LlamaIndex, docling, TesseractOCR, Hugging Face Transformers, etc.
Cloud Computing: Experience with AWS, Azure, or Google Cloud Platform for model training and deployment. Familiarity with Docker and Kubernetes for managing containerized applications.
Version Control: Proficient in using Git for version control and collaboration in software development.
Deployment and Integration:
- Familiarity with frameworks like Flask, FastAPI, or Django for creating and managing APIs.
- Experience in designing and building RESTful APIs for deploying AI models and integrating them with applications.
Other Skills: NLP, Computer Vision and Reinforcement Learning. Strong problem-solving and analytical skills with excellent communication and presentation skills.
Domain Requirements:
- It would be preferable to have exposure to banking domain via past working experiences with Bank and Financial organizations.
- Knowledge in the areas of Core Banking, Retail banking and services such as Deposits, Loans (Home Loans, Mortgages, Personal Loans), Credit Cards, Overdrafts, etc.
- Analytics use cases such as Hyper personalization – Next Best Offer/Next Best Action, customer profiling and segmentation, campaign offer generation etc.
Disclaimer:
- The following job description serves as an informative reference for the tasks you may be required to perform. However, it does not constitute an integral component of your employment agreement and is subject to periodic modifications to align with evolving circumstances.
Skills
What you’ll need to have:
- Bachelors/Master’s degree in Computer science/ Data Science/ AI-ML.
- 6-8 years of hands-on experience in AI, GenAI, Agentic AI, & NLP.
- 3-5 years of experience in Core Banking analytics use cases.
- Extensive experience in handling big datasets structured /unstructured.
- Extensive experience in Banking and Finance Fundamentals.
- They should also have excellent problem-solving and communication skills, as well as a commitment to delivering high-quality results.
