Data Scientist - AI/ML and Generative AI Specialist

Infosys; Bengaluru; Vor Ort; INR 1.400.000 - 2.200.000; Vollzeit

Zusammenfassung

Infosys in Bengaluru is seeking a Data Scientist to design, build and deploy scalable AI/ML solutions leveraging hyperscale cloud platforms (Azure, AWS, GCP) and foundation models.

You will develop end-to-end pipelines, fine-tune LLMs, implement AI guardrails, and collaborate with teams to deliver measurable business value and robust documentation.

Qualifikationen

• Expertise in designing, building and deploying ML models on hyperscalers (Azure, AWS, GCP or Databricks).
• Experience implementing Generative AI models for business solutions on major platforms.
• Proficient in Python with robust, production-grade code.
• Developing frameworks/pipelines to retrieve, optimize and deploy open-source models.
• Experience designing reference architectures for virtual assistants using foundation models.
• Familiarity with deep learning frameworks (Keras, TensorFlow, PyTorch) and libraries (scikit-learn, spacy, gensim, CoreNLP).
• Understanding of LLMs and GenAI applied to text and image analysis.
• Experience fine-tuning LLMs and implementing AI guardrails and Responsible AI.

Aufgaben

• Invent, research, envision, design, and deliver AI/ML applications at scale delivering measurable value.
• Build end-to-end AI/ML solutions: develop, refine, implement, customize and deploy state-of-the-art ML models.
• Design, develop, and research ML systems and schemas through data science prototypes.
• Pursue continuous learning and certifications.
• Cultivate an incubation mindset with quick POCs and ideation.
• Communicate and document work; present to clients and stakeholders.
• Solve real-world problems with technical depth and business awareness.

Kenntnisse

Cloud ML models

Generative AI models

Python programming

End-to-end AI/ML pipelines

Foundation models architecture

Deep learning frameworks

LLMs & GenAI

LLM fine-tuning

LangChain Frameworks

Linux

REST APIs

Cloud platforms (GCP/AWS/Azure)

JIRA

Conflence

Tools

JIRA

Conflence

Jobbeschreibung

RGM - Data Scientist

SKILLS - MUST HAVE:

• Design, build, and deploy Hyperscalers-based (Azure, AWS, GCP or Databricks) ML models, including large-scale data processing, computationally intensive statistical modeling, and advanced analytics - Expert
• Implementation of Generative AI models for business solutions and experience on Azure Open AI, AWS Bedrock or Vertex AI or open-source models - Expert
• Python programming with robust code - Expert
• Developing a framework or generic pipeline to retrieve, optimize, and deploy Open-Source Models - Expert
• Explore and design a reference architecture for developing virtual assistants using foundation models - Expert
• Familiarity with deep learning, machine learning and frameworks (like Keras, TensorFlow or PyTorch etc.), HuggingFace Transformers and libraries (like scikit-learn, spacy, gensim, CoreNLP etc.) - Working knowledge
• Understanding of LLMs and Gen AI especially as applied to text and image analysis and training - Working knowledge
• Experienced in fine-tuning of LLM models, implementation of AI Guardrails and Responsible AI Framework (explainability, bias detection, hallucination control) - Working knowledge
• Experienced in implementing LangChain Frameworks - Working knowledge
• Linux, HTTP/ REST - Working knowledge
• Cloud Technologies - At least one of GCP, AWS, Azure
• JIRA, Conflence - Working knowledge

SKILLS - GOOD TO HAVE:

• Linux shell-scripting
• Multilingual NLP

SOFT SKILLS:

• Good communication
• Ability to work in a team as well as independently deliver modules
• Team player

LEADERSHIP SKILLS:

• People Leadership: Able to lead and mentor a team of ~10-15 people
• Thought Leadership: Having papers published in renowned journals, presentations in conferences, patent-filing preferred

RESPONSIBILITIES:

• Invent, research, envision, design, solution and deliver AI/ ML applications at scale delivering measurable value
• Build end-to-end AI/ ML solutions: Develop, refine, implement, customize and deploy state-of-the-art Machine Learning algorithms and systems, and AI models
• Designing, developing, and researching Machine Learning systems, models, and schemas through data science and data analytics prototypes.
• Continuous learning - Certifications.
• Incubation mindset - Research oriented, ability to deliver quick POC's, and come up with ideas.
• Communication and Documentation - Ability to share knowledge, conduct presentations and sessions, talk to clients and stakeholders, write good-quality technical documentation.
• Problem Solving - Technical depth in solving real-world problems with appreciation of business imperatives.