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.
コグニザントについて
コグニザント（NASDAQ: CTSH）は、AI Builderおよびテクノロジーサービスプロバイダーとして、お客様にフルスタックのAIソリューションを構築することで、AI投資と企業価値を結ぶ架け橋となっています。業界、ビジネスプロセス、エンジニアリングに関する当社の深い専門知識を活かし、組織固有のビジネス環境をテクノロジー・システムに組み込みます。これにより、人間の可能性を最大限に引き出し、確かな成果を実現するとともに、急速に変化する世界においてグローバル企業が常に一歩先を行くための支援を行っています。 詳細については、cognizant.ai をご覧ください。
雇用に関する追加情報
本募集に記載されている報酬情報は、掲載日時点で正確なものです。Cognizantは、適用される法令に従い、いつでも本情報を変更する権利を留保します。
応募者は、対面またはビデオ会議による面接への参加を求められる場合があります。また、各面接の際に、現在有効な州政府または政府発行の身分証明書の提示を求められる場合があります。
Cognizantは機会均等雇用主です。応募および選考において、人種、肌の色、性別、宗教、信条、性的指向、性自認、国籍、障がい、遺伝情報、妊娠、退役軍人の地位、その他連邦法・州法・地方自治体の法律により保護されるいかなる特性に基づく差別も行いません。
