Data Science & AI/ML Lead
About the role
As a Data Science & AI/ML Lead, you will make an impact by leading the design, development, and optimization of enterprise AI solutions that transform experimental models into scalable, production-grade capabilities. You will be a valued member of the AI Engineering team and work collaboratively with architects, data engineers, cloud specialists, and business stakeholders to deliver innovative AI-powered solutions.
In this role, you will:
- Lead the development of AI and machine learning solutions, including data preparation, model training, fine-tuning, and deployment strategies.
- Design and implement scalable data pipelines to curate, cleanse, and prepare structured and unstructured data for machine learning and foundation model training.
- Build and optimize complex agentic AI workflows using modern orchestration frameworks to drive intelligent automation and decision-making.
- Architect advanced Retrieval-Augmented Generation (RAG) solutions, including semantic search, vector embeddings, re-ranking strategies, and document retrieval optimization.
- Establish robust evaluation and benchmarking frameworks to measure model accuracy, reliability, safety, and performance while collaborating on cloud-native AI deployments.
Work model
For Hybrid Roles
We believe hybrid work is the way forward as we strive to provide flexibility wherever possible. Based on this role’s business requirements, this is a hybrid position requiring [X] days a week in a client or Cognizant office in [Location]. Regardless of your working arrangement, we are here to support a healthy work-life balance through our various wellbeing programs.
The working arrangements for this role are accurate as of the date of posting. This may change based on the project you're engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations.
What you need to have to be considered
- 10+ years of experience in Data Science, Machine Learning, or AI Engineering, including experience preparing and managing large-scale datasets.
- Expert-level proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, and Scikit-learn.
- Hands-on experience with large language models (LLMs), small language models (SLMs), prompt engineering, and agentic AI frameworks.
- Strong knowledge of vector databases, semantic search architectures, and SQL/NoSQL data platforms.
- Experience working with cloud AI platforms such as Azure AI Foundry, Vertex AI, or Amazon SageMaker, including model deployment and operationalization.
These will help you stand out
- Experience implementing advanced RAG architectures and enterprise search solutions.
- Expertise in model fine-tuning techniques such as LoRA, PEFT, and hyperparameter optimization.
- Experience establishing AI evaluation and benchmarking frameworks using tools such as RAGAS or TruLens.
- Knowledge of synthetic data generation, data labeling strategies, and responsible AI practices including bias mitigation.
- Experience deploying AI solutions in cloud-native and containerized environments across Azure, AWS, or Google Cloud Platform.
关于高知特 (Cognizant)
高知特(Cognizant)（纳斯达克代码：CTSH）作为一家AI Builder和相关技术服务提供商，致力于通过打造全栈AI解决方案，帮助企业将人工智能投资转化为实际价值。公司凭借深厚的行业经验、流程优化和工程技术专长，将企业独特的业务场景融入科技系统，赋能组织释放人才潜能，推动切实成果，并帮助全球企业在瞬息万变的环境中保持领先。如需了解更多详情，敬请访问 cognizant.ai 或关注@cognizant。
补充雇佣信息
薪酬信息截至本职位发布之日为准。Cognizant 保留在适用法律允许的范围内随时修改该信息的权利。
申请人可能需要通过现场面试或视频会议的方式参加面试。此外，候选人在每次面试时可能需要出示其当前所在州或政府签发的有效身份证件。
Cognizant 是一家提供平等就业机会的雇主。在招聘过程中，您的申请和候选资格不会因种族、肤色、性别、宗教、信仰、性取向、性别认同、国籍、残疾、遗传信息、怀孕、退伍军人身份或任何其他受联邦、州或地方法律保护的特征而受到影响。
