"Please note, this role is not able to offer visa transfer or sponsorship now or in the future."
About the role
As a Senior MLOps Engineer, you will make an impact by designing, implementing, and managing the cloud infrastructure, deployment pipelines, and monitoring frameworks that enable machine learning models to run reliably and efficiently in production environments. You will be a valued member of the AI & Data Engineering team and work collaboratively with Data Scientists, Data Engineers, business stakeholders, and global delivery teams to establish and scale MLOps capabilities on Google Cloud Platform (GCP).
In this role, you will:
- Lead the migration, containerization, and deployment of existing machine learning models into the Google Cloud Vertex AI ecosystem.
- Design, implement, and maintain scalable CI/CD/CT pipelines using Vertex AI Pipelines, Kubeflow, Cloud Build, and related cloud-native technologies.
- Develop and manage model deployment frameworks supporting both real-time and batch inference workloads while ensuring reliability, scalability, and performance.
- Establish monitoring, governance, and lifecycle management processes, including model drift detection, version control, model registry management, and rollback strategies.
- Partner with business stakeholders, Data Science teams, and Data Engineering teams to define requirements, align priorities, and deliver enterprise-grade MLOps solutions.
Work model
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 regular onsite presence in Atlanta, Georgia. 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
- 7+ years of experience in Data Engineering, Software Engineering, Machine Learning Engineering, or a related technical field.
- 3+ years of hands-on experience building and managing MLOps solutions and deploying machine learning models into production environments.
- Strong expertise with Google Cloud Platform services, including Vertex AI, BigQuery, Cloud Storage, Pub/Sub, and related cloud-native technologies.
- Advanced programming experience with Python and SQL, along with hands-on expertise in Docker, Kubernetes, and Google Kubernetes Engine (GKE).
- Proven experience implementing CI/CD pipelines and Infrastructure as Code using tools such as Terraform, GitHub Actions, GitLab CI, Jenkins, or Cloud Build.
- Demonstrated ability to lead technical initiatives, collaborate across distributed teams, and communicate effectively with both technical and non-technical stakeholders.
These will help you stand out
- Google Cloud Professional Machine Learning Engineer or Professional Cloud Architect certification.
- Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-Learn.
- Experience implementing model monitoring, governance, and compliance frameworks in enterprise environments.
- Familiarity with Agile and Scrum methodologies.
- Experience mentoring engineers and leading offshore or distributed delivery teams.
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 September 29th, 2026.
Salary and Other Compensation:
The annual salary for this position is between $130,000 - $155,000 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
- 401(k) plan and contributions
- Long-term/Short-term Disability
- Paid Parental Leave
- Employee Stock Purchase Plan
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.
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。
