.jpg)
Machine Learning Specialist
Posted 5 days ago by PRIMUS Global Solutions (PRIMUS UK & Europe)
Negotiable
Undetermined
Undetermined
Bromley, England, United Kingdom
Summary: The role of Senior AI/ML & Generative AI Engineer at Infosys involves designing, developing, and deploying advanced AI solutions, with a focus on Python development and cloud platforms. The position requires collaboration with clients to address complex business challenges and architect scalable AI solutions. Candidates will work with cutting-edge technologies in Generative AI and LLM fine-tuning, contributing to impactful consulting solutions across various industries. This role also includes leading project efforts and guiding teams in AI/ML solution development.
Key Responsibilities:
- Anchor the engagement effort from business process consulting and problem definition to solution design, development, and deployment.
- Lead the discovery and definition of AI/ML solutions and guide teams on project processes and deliverables.
- Act as a thought leader in your domain, advising on architecture and design reviews.
- Drive business pursuit initiatives, client training, and in-house capability building.
- Shape value-adding consulting solutions that help clients meet evolving business needs.
- Develop the core Python Programs using OOPs Concepts.
- Design and develop scalable AI/ML solutions using Python and cloud platforms.
- Lead the implementation of Generative AI models, LLMs, and agentic frameworks.
- Collaborate with stakeholders to define problem statements and solution approaches.
- Deploy models using MLOps tools such as SageMaker, Snowflake, and CI/CD pipelines.
- Integrate vector databases and Retrieval-Augmented Generation (RAG) pipelines.
- Ensure high-quality delivery and adherence to best practices in AI/ML engineering.
Key Skills:
- Deep expertise in AI/ML and Generative AI technologies.
- Proficiency in Python development and OOPs concepts.
- Experience with Large Language Models (LLMs) and agentic AI architectures.
- Familiarity with cloud platforms such as AWS, Azure ML, and GCP AI Services.
- Knowledge of MLOps tools and CI/CD pipelines.
- Strong problem-solving and consulting skills.
- Ability to collaborate with clients and stakeholders effectively.
- Experience in developing scalable AI solutions.
Salary (Rate): undetermined
City: Bromley
Country: United Kingdom
Working Arrangements: undetermined
IR35 Status: undetermined
Seniority Level: Senior
Industry: IT
Infosys is seeking a Senior AI/ML & Generative AI Engineer with deep expertise in designing, developing, and deploying advanced AI solutions. This includes core Python development using OOPs concepts, Large Language Models (LLMs), and Agentic AI architectures. The ideal candidate will collaborate with clients to understand complex business challenges, architect scalable AI solutions, and deploy them using modern cloud platforms such as AWS, Azure ML and GCP AI Services. This role offers the opportunity to work on cutting-edge technologies in Generative AI, LLM fine-tuning, agentic orchestration, and vector databases, while shaping impactful consulting solutions across industries like Banking, Finance, and Capital Markets.
Your Role As a Senior Lead Analyst, you will:
- Anchor the engagement effort from business process consulting and problem definition to solution design, development, and deployment.
- Lead the discovery and definition of AI/ML solutions and guide teams on project processes and deliverables.
- Act as a thought leader in your domain, advising on architecture and design reviews.
- Drive business pursuit initiatives, client training, and in-house capability building.
- Shape value-adding consulting solutions that help clients meet evolving business needs.
Responsibilities
- Develop the core Python Programs using oops Concepts.
- Design and develop scalable AI/ML solutions using Python and cloud platforms.
- Lead the implementation of Generative AI models, LLMs, and agentic frameworks.
- Collaborate with stakeholders to define problem statements and solution approaches.
- Deploy models using MLOps tools such as SageMaker, Snowflake, and CI/CD pipelines.
- Integrate vector databases and Retrieval-Augmented Generation (RAG) pipelines.
- Ensure high-quality delivery and adherence to best practices in AI/ML engineering.