Capgemini
We are seeking a highly skilled Computer Vision Engineer with strong system-level engineering capabilities and hands‑on experience building, deploying, and optimizing computer vision workloads in production environments. The ideal candidate combines deep technical expertise across cloud infrastructure, AI/ML frameworks, and containerized deployments with the ability to deliver scalable, reliable, and secure CV solutions. This role requires strong ownership, cross‑functional collaboration, and the ability to support end‑to‑end model lifecycle—from research and development through deployment and monitoring.
Key Responsibilities
Design, develop, and deploy computer vision models for object detection, image segmentation, classification, and video analytics, using frameworks such as PyTorch or TensorFlow.
Build scalable pipelines for training, inference, and model serving, leveraging containerization (Docker) and orchestration frameworks.
Develop and manage CI/CD workflows (Jenkins, GitHub Actions, GitLab CI) to automate model integration, validation, and deployment.
Engineer robust system‑level architectures on GCP (preferred) including Compute Engine, Cloud Storage, GKE, AI Platform, IAM, VPC networking, and logging/monitoring services.
Implement REST‑based model serving using FastAPI, Flask, or TensorFlow Serving to support real‑time and batch inference.
Ensure infrastructure reliability through strong foundations in Linux systems, networking concepts, and general cloud security best practices.
Collaborate with data engineering, platform, and product teams to deliver optimized, production‑ready CV applications.
Support performance tuning, resource optimization, and incident troubleshooting across development, staging, and production environments.
Maintain high standards for code quality, documentation, and compliance, including considerations for data privacy and PII handling.
Core Skill Requirements
System‑Level Expertise
Docker containerization and production‑grade deployment workflows
CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI)
Strong proficiency in Linux; familiarity with Windows environments
Networking fundamentals: DNS, VPNs, firewalls, VPC routing
Cloud engineering with GCP (Compute Engine, Cloud Storage, AI Platform, GKE, IAM, VPC, monitoring)
AI & Computer Vision Fundamentals
Expertise in object detection, segmentation, classification, and video analytics
Strong experience with CNNs and deep learning frameworks (PyTorch or TensorFlow)
Model deployment and serving via REST APIs (FastAPI, Flask, TensorFlow Serving)
Bonus Skills (Nice to Have)
MLOps tools: MLFlow, Kubeflow, Airflow
Monitoring/logging stacks: Prometheus, Grafana, ELK
Understanding of security, data privacy, and PII governance
Experience with distributed model training or GPU optimization
Qualifications
Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, AI/ML, or related discipline
5+ years of experience in computer vision, machine learning, or AI systems engineering
Proven experience deploying production CV models in cloud environments
Strong analytical, debugging, and problem‑solving skills
Demonstrated ability to work independently and lead technical initiatives
Pay range: $42.35/hour - $66.18/hour. Benefits include medical, dental, vision and retirement benefits. Applications will be accepted on an ongoing basis.
Tundra Technical Solutions is among North America’s leading providers of Staffing and Consulting Services. Our success and our clients’ success are built on a foundation of service excellence. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Unincorporated LA County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: client provided property, including hardware (both of which may include data) entrusted to you from theft, loss or damage; return all portable client computer hardware in your possession (including the data contained therein) upon completion of the assignment, and; maintain the confidentiality of client proprietary, confidential, or non‑public information. In addition, job duties require access to secure and protected client information technology systems and related data security obligations.
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Key Responsibilities
Design, develop, and deploy computer vision models for object detection, image segmentation, classification, and video analytics, using frameworks such as PyTorch or TensorFlow.
Build scalable pipelines for training, inference, and model serving, leveraging containerization (Docker) and orchestration frameworks.
Develop and manage CI/CD workflows (Jenkins, GitHub Actions, GitLab CI) to automate model integration, validation, and deployment.
Engineer robust system‑level architectures on GCP (preferred) including Compute Engine, Cloud Storage, GKE, AI Platform, IAM, VPC networking, and logging/monitoring services.
Implement REST‑based model serving using FastAPI, Flask, or TensorFlow Serving to support real‑time and batch inference.
Ensure infrastructure reliability through strong foundations in Linux systems, networking concepts, and general cloud security best practices.
Collaborate with data engineering, platform, and product teams to deliver optimized, production‑ready CV applications.
Support performance tuning, resource optimization, and incident troubleshooting across development, staging, and production environments.
Maintain high standards for code quality, documentation, and compliance, including considerations for data privacy and PII handling.
Core Skill Requirements
System‑Level Expertise
Docker containerization and production‑grade deployment workflows
CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI)
Strong proficiency in Linux; familiarity with Windows environments
Networking fundamentals: DNS, VPNs, firewalls, VPC routing
Cloud engineering with GCP (Compute Engine, Cloud Storage, AI Platform, GKE, IAM, VPC, monitoring)
AI & Computer Vision Fundamentals
Expertise in object detection, segmentation, classification, and video analytics
Strong experience with CNNs and deep learning frameworks (PyTorch or TensorFlow)
Model deployment and serving via REST APIs (FastAPI, Flask, TensorFlow Serving)
Bonus Skills (Nice to Have)
MLOps tools: MLFlow, Kubeflow, Airflow
Monitoring/logging stacks: Prometheus, Grafana, ELK
Understanding of security, data privacy, and PII governance
Experience with distributed model training or GPU optimization
Qualifications
Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, AI/ML, or related discipline
5+ years of experience in computer vision, machine learning, or AI systems engineering
Proven experience deploying production CV models in cloud environments
Strong analytical, debugging, and problem‑solving skills
Demonstrated ability to work independently and lead technical initiatives
Pay range: $42.35/hour - $66.18/hour. Benefits include medical, dental, vision and retirement benefits. Applications will be accepted on an ongoing basis.
Tundra Technical Solutions is among North America’s leading providers of Staffing and Consulting Services. Our success and our clients’ success are built on a foundation of service excellence. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Unincorporated LA County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: client provided property, including hardware (both of which may include data) entrusted to you from theft, loss or damage; return all portable client computer hardware in your possession (including the data contained therein) upon completion of the assignment, and; maintain the confidentiality of client proprietary, confidential, or non‑public information. In addition, job duties require access to secure and protected client information technology systems and related data security obligations.
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