Senior Associate L2 - DS-AI & Machine Learning

Publicis Sapient is looking for a highly capable Machine Learning Engineer to join its Data CoE. As part of the team, you will be responsible for creating data-driven solutions. You will be working on various MLOps stages namely deployment, governance, reproducibility, and monitoring of ML models. You will be evaluating new or existing machine learning (ML) processes, performing statistical analysis to resolve data set problems, and enhancing the accuracy of our AI software s predictive automation capabilities. You will be participating in the development of machine learning apps that meet business needs. You will also communicate with clients and stakeholders to understand business objectives and how to achieve them using machine learning.

Your Impact:

• As a Senior Data Scientist specializing in Generative AI, you will:
• Shape Next-Generation Solutions: Partner with cross-functional teams to design and implement AI-driven systems that transform user experiences and streamline business processes.
• Enhance AI Through Data: Employ data-centric methodologies to improve model accuracy and responsiveness by curating high-quality datasets and optimizing real-time performance.
• Finetune Industry-Specific Gen AI Models: Adapt and fine-tune large language models for domain-specific applications using advanced techniques like instruction tuning, domain adaptation, and reinforcement learning from human feedback (RLHF).
• Develop Intelligent AI Agents: Architect and refine AI agents that solve complex business challenges, leveraging LLMs to deliver personalized, user-centric solutions.
• Advance Generative AI Applications: Innovate with cutting-edge generative AI models such as LLM, VLM, GANs, and VAEs to create tailored applications for dynamic content creation, predictive analytics, and enhanced automation.
• Scale AI with Cloud Technology: Deploy and scale LLM-based solutions on platforms like GCP, AWS and Azure to address real-world business problems with precision and efficiency.

Qualifications

Your Skills & Experience:

• Bachelor s degree in computer science, data science, mathematics, or a related field.
• At least two years experience as a machine learning engineer.
• Advanced proficiency with Python, Java, and R code writing.
• Extensive knowledge of ML frameworks, libraries, data structures, data modeling, and software architecture.
• In-depth knowledge of mathematics, statistics, and algorithms.
• Superb analytical and problem-solving abilities. Set Yourself Apart With:
• Experience in Docker, Kubernetes, Kubeflow, MLflow, DVC, Cloud platforms
• ML Model deployments and serving
• Model Monitoring, Management and Governance
• ML Feature Store and Artefact Store
• Orchestration and ML Pipelines