Gen AI Engineer Full-time

Job Description

Infosys is seeking a Gen AI engineer with machine learning and Python experience. You will work on productionizing E2E Gen AI solutions, Agentic AI frameworks, machine learning models and guide development team for implementing end to end machine learning use case. They will define end to end architecture of Data Science and machine learning project along with being the technology architect. The candidate will provide technology consulting for defining right Generative AI, Agentic AI, Data Science and ML use cases.

Basic Qualification :

• Bachelor’s degree or foreign equivalent required from an accredited institution. Will also consider three years of progressive experience in the specialty in lieu of every year of education.
• At least 2 years of experience with Information Technology
• Candidate must be located within commuting distance of Raleigh, NC / Richardson, TX / Houston, TX / Tempe, AZ / Phoenix, AZ / Alpharetta, GA or be willing to relocate. This position may require travel.

Required:

• At least 2 years of NLP analysis skills, software engineering or systems analysis experience preferred
• Programming – Python, R
• Machine Learning – strong fundamentals in machine learning
• Deep Learning – experience with CNNs, RNN, LSTMs and the latest research trends
• Experience with Lean / Agile development methodologies
• 2 years of hands on experience with more than one programming language; Python, R, Scala, Java, SQL
• Experience in productionizing Gen AI technologies, Advanced RAG based implementations,
• Strong programming skills, strong IT background
• Demonstrated experience working with Large Language Models (LLMs), AWS, Azure, or Google cloud infrastructure
• Proficiency in developing full stack applications and API services.
• Proficiency in processing/ingesting unstructured data from PDFs, HTML, Image files, audio to text etc.
• Knowledge in vector databases and methods to tune vector search and retrieval process to improve accuracy and reduce latency.
• Knowledge in Model evaluation tools like DeepEval, FMeval, RAGAS , Bedrock model evaluation.
• Experience with data gathering, data quality, system architecture, coding best practices
• Big Data Experience strongly preferred – HDFS, Hive, Spark, Scala
• Experience with perception (e.g. computer vision), time series data (e.g. text analysis)
• Data visualization tools such as Tableau, Query languages such as SQL, Hive
• Good applied statistics skills, such as distributions, statistical testing, regression, etc.
• Experience and desire to work in a Global delivery environment.

The job entails an extensive amount of travel. The job also entails sitting as well as working at a computer for extended periods of time. Should be able to communicate by telephone, email or face to face.

Skillset

Domain(IBPO) Analytics- Data science Statistical Tools, Technology Artificial Intelligence Artificial Intelligence – ALL, Technology Data Science Machine Learning

EEO/About Us

Infosys is a global leader in next-generation digital services and consulting. We enable clients in more than 50 countries to navigate their digital transformation. With over four decades of experience in managing the systems and workings of global enterprises, we expertly steer our clients through their digital journey. We do it by enabling the enterprise with an AI-powered core that helps prioritize the execution of change. We also empower the business with agile digital at scale to deliver unprecedented levels of performance and customer delight. Our always-on learning agenda drives their continuous improvement through building and transferring digital skills, expertise and ideas from our innovation ecosystem.

Infosys provides equal employment opportunities to applicants and employees without regard to race; color; sex; gender identity; sexual orientation; religious practices and observances; national origin; pregnancy, childbirth, or related medical conditions; status as a protected veteran or spouse/family member of a protected veteran; or disability.