Top AI & Machine Learning Jobs

Build and deploy AI and machine learning solutions using distributed computing, cloud platforms, data pipelines, and production-grade software engineering practices. Responsibilities include technical requirements analysis, feature development, testing, code reviews, agile collaboration, architecture validation, and prototyping emerging technologies. The role partners with data scientists, architects, client-facing teams, and clients to deliver scalable AI solutions and manage machine learning lifecycles.

Build and optimize production-grade LLM and generative AI systems, including RAG pipelines, model fine-tuning, embedding search, evaluation, and scalable inference. Develop FastAPI services, integrate AI into production software, and improve latency, GPU utilization, reliability, and cost efficiency. Research emerging AI techniques, contribute to MLOps through model tracking and observability, and collaborate with clients and cross-functional teams.

Designs and builds production-grade AI applications natively on Snowflake using Cortex Analyst, Cortex Search, Snowflake Agents, semantic models, Python, and SQL. Develops secure, performant natural-language querying, retrieval, text-to-SQL, and agentic workflows over governed data. Owns delivery of a technical workstream, collaborates with data scientists, engineers, clients, and stakeholders, and supports enterprise GenAI and analytics solutions. Snowflake implementation experience is mandatory; regulated-industry experience is advantageous.

Develop advanced algorithms and apply statistical, data mining, machine learning, and AI techniques to large structured and unstructured datasets. Identify trends, evaluate emerging data technologies, and communicate analytical findings to clients and ZS stakeholders. The role requires collaboration across multiple projects, strong quantitative and research skills, and proficiency with Python, SQL, Pandas, and PySpark. Client-facing work may require travel.

Lead teams to build scalable AI applications, develop client relationships, manage budgets, and mentor talent in the AI field.

Lead AI strategy and client engagements for life sciences clients, drive AI and cloud data strategy, manage and mentor consulting teams, engage C-suite stakeholders, oversee risk and delivery, and build AI-capable practices across the firm.

The Advanced Data Science Manager leads a team of data scientists, develops data science strategies, manages client projects, and drives business development while providing thought leadership and mentoring.

As an AI Engineering Lead, you'll shape AI operations, develop strategies, mentor a team, and integrate AI technologies into operations for impactful outcomes.

The Lead AI Scientist will design and optimize LLM architectures, fine-tune models, develop AI systems, mentor junior members, and collaborate with clients and teams on AI solutions.

In this role, you will design and deploy advanced machine learning and Generative AI solutions, leading projects from conception to deployment while mentoring junior team members.