VML Lead Data Scientist Deep Learning/Machine Learning

Job description

<p><p><b>Description : </b></p><br/><p><b>About the job :</b></p><br/><p><b>Who We Are :</b></p><br/><p>At VML, we are a beacon of innovation and growth in an ever-evolving world.</p><br/><p>Our heritage is built upon a century of combined expertise, where creativity meets technology, and diverse perspectives ignite inspiration.</p><br/><p>With the merger of VMLY&R and Wunderman Thompson, we have forged a new path as a growth partner that is part creative agency, part consultancy, and part technology powerhouse.</p><br/><p>Our global family now encompasses over 30,000 employees across 150+ offices in 64 markets, each contributing to a culture that values connection, belonging, and the power of differences.</p><br/><p>Our expertise spans the entire customer journey, offering deep insights in communications, commerce, consultancy, CRM, CX, data, production, and technology.</p><br/><p>We deliver end-to-end solutions that result in revolutionary work.</p><br/><p><b>Lead Data Scientist</b></p><br/><p>Permanent - India</p><br/><p><b>The Opportunity :</b></p> <br/><p>We are investing massively in developing next-generation AI tools for multimodal datasets and a wide range of applications.</p><br/><p>We are building large scale, enterprise grade solutions and serving these innovations to our clients and WPP agency partners.</p><br/><p>As a member of our team, you will work alongside world-class talent in an environment that not only fosters innovation but also personal and professional growth.</p><br/><p>You will be at the forefront of AI, leveraging multimodal datasets to build groundbreaking AI systems over a multi-year roadmap.</p><br/><p>Your contributions will directly shape cutting-edge AI products and services that make a tangible impact for FTSE 100 clients.</p><br/><p>We are hiring across all experience levels in AI engineering, from entry-level to seasoned professionals, and offer competitive salaries commensurate with experience and skills.</p><br/><p><b>What Youll Be Doing :</b></p><br/><p>- Design and deploy intelligent, agent-driven systems that autonomously solve complex, real-world problems using cutting-edge algorithms and AI libraries.</p><br/><p>- Engineer collaborative agentic frameworks that coordinate multiple specialized agents to deliver advanced AI capabilities for enterprise-scale applications.</p><br/><p>- Build and extend MCP-based infrastructure that enables secure, context-rich interaction between agents and external tools, empowering AI systems to act, reason, and adapt in real-time.</p><br/><p>- Build human-in-the-loop agent workflows where humans benefit from AI assistance in decision-making and automation, while agents learn and improve through continuous human feedback.</p><br/><p>- Stay abreast of the latest trends in AI research and integrate them into our products and services.</p><br/><p>- Communicate technical challenges and solutions to non-technical stakeholders and team members.</p><br/><p><b>What We Want From You :</b></p><br/><p>- Fluency in Python and experience with core machine learning and deep learning frameworks (e.g., PyTorch, TensorFlow), with a proven ability to build, train, and evaluate models in real-world environments.</p><br/><p>- Experience of managing a team</p><br/><p>- Solid grasp of modern ML/AI fundamentals, including representation learning, optimization, generalization, and evaluation metrics across supervised, unsupervised, and generative settings.</p><br/><p>- Experience working with multimodal data, including text, image, and structured formats, and building pipelines for feature extraction, embedding generation, and downstream model consumption.</p><br/><p>- Hands-on experience integrating AI models into production workflows, including model inference, API deployment, and system monitoring.</p><br/><p>- Proficiency in using version control, testing frameworks, and collaborative development workflows, including Git and basic CI/CD practices.</p><br/><p>- Ability to communicate clearly about system behavior, trade-offs, and architectural decisions, especially when working across interdisciplinary teams.</p><br/><p>- Understanding of LLMOps/MLOps principles, including model/version tracking, pipeline reproducibility, observability, and governance in production environments</p><br/><p><b>If You Know Some Of This Even Better :</b></p><br/><p>- Experience designing agentic systems, including goal-oriented multi-agent workflows, agent coordination strategies, and state/context management across long-running processes.</p><br/><p>- Proficiency in agent orchestration frameworks such as LangChain, LangGraph, AutoGen, or custom frameworks designed to enable modular, reusable, and stateful agent components.</p><br/><p>- Experience implementing secure agent-tool communication via infrastructures like Model Context Protocol (MCP), enabling agents to operate over filesystems, command-line tools, cloud APIs, and databases.</p><br/><p>- Comfort with designing systems that evolve through human feedback, including methods like reinforcement learning from human feedback (RLHF), reward modeling, and in-context human correction.</p><br/><p>- Competence in scalable deployment practices, including containerization (Docker), orchestration (Kubernetes), and cloud-native tools across AWS, GCP, or Azure</p><br/></p> (ref:hirist.tech)

Required Skill Profession

Mathematical Science Occupations