Applied Scientist

This role is for one of the Weekday's clients

Salary range: Rs 8000000 - Rs 14000000 (ie INR 80-140 LPA)

Experience: 13+ yrs

Location: Bengaluru, Chennai

Job Type: full-time

We are seeking a highly accomplished Applied Scientist to lead the design, development, and deployment of cutting-edge Artificial Intelligence solutions with a strong focus on Agentic AI, Large Language Models (LLMs), and Recommendation Systems. This role is ideal for an experienced AI professional who is passionate about transforming advanced research into scalable, production-grade products that create measurable business impact.

As an Applied Scientist, you will work at the intersection of machine learning, generative AI, personalization, and intelligent automation. You will be responsible for driving innovation across AI-powered products, building sophisticated recommendation engines, developing autonomous AI agents, and leveraging state-of-the-art LLMs to solve complex real-world problems. You will collaborate closely with engineering, product, data science, and business teams to translate strategic objectives into scalable AI solutions.

The role requires a strong blend of research depth, engineering mindset, and business acumen. You will evaluate emerging AI technologies, define scientific roadmaps, establish best practices for model development, and mentor teams working on advanced machine learning initiatives. The ideal candidate possesses extensive experience in machine learning systems, deep learning, recommendation technologies, and modern AI architectures while maintaining a strong focus on product outcomes and customer value.

Requirements

Key Responsibilities

AI Research & Innovation

• Lead the research, design, and implementation of advanced AI and machine learning solutions.
• Drive innovation in Agentic AI systems capable of autonomous reasoning, planning, decision-making, and task execution.
• Evaluate emerging AI technologies, frameworks, and methodologies to identify opportunities for product differentiation and business growth.
• Define AI strategy and contribute to long-term scientific and technical roadmaps.

Large Language Models & Generative AI

• Develop, fine-tune, evaluate, and optimize Large Language Models for enterprise-scale applications.
• Design LLM-powered workflows including Retrieval-Augmented Generation (RAG), tool calling, orchestration frameworks, and multi-agent systems.
• Build intelligent conversational systems, reasoning engines, knowledge assistants, and automation solutions.
• Establish evaluation frameworks to measure model quality, safety, performance, and business impact.

Recommendation Systems & Personalization

• Architect and develop large-scale recommendation engines that deliver personalized user experiences.
• Implement collaborative filtering, content-based recommendation models, ranking algorithms, reinforcement learning approaches, and hybrid recommendation techniques.
• Design experimentation frameworks and continuously optimize recommendation performance through data-driven insights.
• Collaborate with product teams to improve customer engagement, retention, and conversion metrics through personalization initiatives.

Machine Learning Engineering

• Build scalable machine learning pipelines for training, inference, deployment, monitoring, and model lifecycle management.
• Partner with engineering teams to productionize AI solutions and ensure operational excellence.
• Drive best practices for model governance, feature engineering, experimentation, and MLOps.
• Optimize AI systems for performance, scalability, reliability, and cost efficiency.

Leadership & Collaboration

• Mentor data scientists, machine learning engineers, and research teams.
• Collaborate with product leaders and stakeholders to define AI-driven business solutions.
• Present technical findings and recommendations to executive leadership and cross-functional teams.
• Foster a culture of innovation, experimentation, and continuous learning across AI initiatives.

What Makes You a Great Fit

• 13+ years of experience in Artificial Intelligence, Machine Learning, Data Science, or Applied Research roles.
• Deep expertise in Agentic AI architectures, autonomous agents, orchestration frameworks, and intelligent automation systems.
• Strong hands-on experience with Large Language Models, Generative AI, prompt engineering, fine-tuning, RAG architectures, and multi-agent workflows.
• Proven experience designing and deploying large-scale Recommendation Systems and personalization platforms.
• Strong foundation in machine learning, deep learning, probability, statistics, optimization, and algorithm design.
• Expertise in Python and modern AI/ML frameworks such as PyTorch, TensorFlow, LangChain, LlamaIndex, Hugging Face, or similar ecosystems.
• Experience building production-grade AI systems that serve large user bases and business-critical applications.
• Strong understanding of MLOps, model deployment, monitoring, and AI governance practices.
• Exposure to Computer Vision technologies, image understanding, video analytics, and multimodal AI systems is highly desirable.
• Knowledge of Natural Language Processing, information retrieval, semantic search, knowledge graphs, and conversational AI is a strong advantage.
• Proven ability to lead cross-functional teams and influence AI strategy across an organization.
• Strong communication, stakeholder management, and problem-solving skills.
• Experience translating research concepts into scalable products that deliver measurable business outcomes.
• Passion for innovation, experimentation, and building next-generation AI-powered experiences.