"Please note, this role is not able to offer visa transfer or sponsorship now or in the future."
About the role
As a Senior Machine Learning Engineer you will make an impact by designing, building, and deploying scalable AI and machine learning solutions that drive business innovation and measurable outcomes. You will be a valued member of the AI & Data Engineering team and work collaboratively with architects, data engineers, product owners, business stakeholders, and cross-functional technology teams.
In this role, you will:
- Design, develop, and deploy machine learning and Generative AI solutions using AWS cloud-native services and modern MLOps practices.
- Build and operationalize end-to-end MLOps pipelines for model training, validation, deployment, monitoring, and lifecycle management using Amazon SageMaker.
- Develop Generative AI applications leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector databases, embeddings, and prompt engineering techniques.
- Implement scalable, secure, and resilient AI/ML platforms using Docker, Kubernetes/EKS, CI/CD pipelines, and Infrastructure as Code practices.
- Partner with technical and business stakeholders to translate requirements into production-ready AI solutions while ensuring performance, reliability, governance, and cost optimization.
Work model
We strive to provide flexibility wherever possible. Based on this role’s business requirements, this position is remote.
The working arrangements for this role are accurate as of the date of posting. This may change based on the project you are engaged in, as well as business and client requirements.
What you need to have to be considered
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
- 6–10 years of software development experience, including at least 3 years in Machine Learning Engineering, AI Engineering, or MLOps.
- Strong proficiency in Python and hands-on experience with AI/ML frameworks such as TensorFlow, PyTorch, Hugging Face, LangChain, or similar technologies.
- Hands-on experience with Amazon SageMaker and AWS AI/ML services for model development, deployment, and monitoring.
- Experience building and supporting MLOps pipelines using CI/CD automation, Infrastructure as Code, and cloud-native development practices.
- Knowledge of Generative AI concepts, including LLMs, prompt engineering, embeddings, vector databases, and RAG architectures.
- Experience with Docker, Kubernetes/EKS, Git, and modern software engineering best practices.
- Strong understanding of machine learning lifecycle management, model governance, observability, and production support.
- Experience working with AWS services such as S3, Lambda, Step Functions, API Gateway, CloudWatch, ECS/EKS, and IAM.
- Strong analytical, problem-solving, collaboration, and communication skills.
This will help you stand out
- Experience designing and deploying enterprise-scale Generative AI solutions.
- Hands-on experience with Amazon Bedrock and foundation models such as OpenAI, Anthropic Claude, Llama, or similar platforms.
- Experience in highly regulated industries such as Healthcare, Insurance, or Financial Services.
- Knowledge of Responsible AI, AI Governance, Model Risk Management, and compliance frameworks.
- Experience with data engineering frameworks and large-scale data processing technologies.
- AWS Certified Machine Learning – Specialty certification.
- AWS Certified Solutions Architect (Associate or Professional) certification.
- AWS Certified Developer – Associate certification.
- Additional certifications in MLOps, AI Engineering, or Generative AI technologies.
We're excited to meet people who share our mission and can make an impact in a variety of ways. Don't hesitate to apply, even if you only meet the minimum requirements listed. Think about your transferable experiences and unique skills that make you stand out as someone who can bring new and exciting things to this role.
Applications will be accepted until 07/27/2026
The annual salary range for this position is between $110.000 – $130.000 depending on experience and other qualifications of the successful candidate.
This position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.
Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:
· Medical/Dental/Vision/Life Insurance
· Paid holidays plus Paid Time Off
· Long-term/Short-term Disability
· Paid Parental Leave
Disclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.
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。
