(Immediate Start) Assistant Manager, ML CV Ops Engineer

Job Description Ready to build the future with AI At Genpact, we don't just keep up with technology-we set the pace. AI and digital innovation are redefining industries, and we're leading the charge. Genpact's AI Gigafactory, our industry-first accelerator, is an example of how we're scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to agentic AI, our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, innovation-driven environment, love building and deploying cutting-edge AI solutions, and want to push the boundaries of what's possible, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation, our teams implement data, technology, and AI to create tomorrow, today. Get to know us at genpact.com and on LinkedIn, X, YouTube, and Facebook. Inviting applications for the role of Assistant Manager, ML CV Ops Engineer We are seeking a highly skilled ML CV Ops Engineer to join our AI Engineering team. This role is focused on operationalizing Computer Vision models-ensuring they are efficiently trained, deployed, monitored, and retrained across scalable infrastructure or edge environments. The ideal candidate has deep technical knowledge of ML infrastructure, DevOps practices, and hands-on experience with CV pipelines in production. You'll work closely with data scientists, DevOps, and software engineers to ensure computer vision models are robust, secure, and production-ready always. Key Responsibilities: End-to-End Pipeline Automation: Build and maintain ML pipelines for computer vision tasks (data ingestion, preprocessing, model training, evaluation, inference). Use tools like MLflow, Kubeflow, DVC, and Airflow to automate workflows. Model Deployment & Serving: Package and deploy CV models using Docker and orchestration platforms like Kubernetes. Use model-serving frameworks (TensorFlow Serving, TorchServe, Triton Inference Server) to enable real-time and batch inference. Monitoring & Observability: Set up model monitoring to detect drift, latency spikes, and performance degradation. Integrate custom metrics and dashboards using Prometheus, Grafana, and similar tools. Model Optimization: Convert and optimize models using ONNX, TensorRT, or OpenVINO for performance and edge deployment. Implement quantization, pruning, and benchmarking pipelines. Edge AI Enablement (Optional but Valuable): Deploy models on edge devices (e.g., NVIDIA Jetson, Coral, Raspberry Pi) and manage updates and logs remotely. Collaboration & Support: Partner with Data Scientists to productionize experiments and guide model selection based on deployment constraints. Work with DevOps to integrate ML models into CI/CD pipelines and cloud-native architecture. Required Qualifications: .Bachelor's or Master's in Computer Science, Engineering, or a related field. .Sound experience in ML engineering, with significant work in computer vision and model operations. .Strong coding skills in Python and familiarity with scripting for automation. .Hands-on experience with PyTorch, TensorFlow, OpenCV, and model lifecycle tools like MLflow, DVC, or SageMaker. .Solid understanding of containerization and orchestration (Docker, Kubernetes). .Experience with cloud services (AWS/GCP/Azure) for model deployment and storage. Preferred Qualifications: .Experience with real-time video analytics or image-based inference systems. .Knowledge of MLOps best practices (model registries, lineage, versioning). .Familiarity with edge AI deployment and acceleration toolkits (e.g., TensorRT, DeepStream). .Exposure to CI/CD pipelines and modern DevOps tooling (Jenkins, GitLab CI, ArgoCD). .Contributions to open-source ML/CV tooling or experience with labeling workflows (CVAT, Label Studio). Why join Genpact .Lead AI-first transformation - Build and scale AI solutions that redefine industries .Make an impact - Drive change for global enterprises and solve business challenges that matter .Accelerate your career-Gain hands-on experience, world-class training, mentorship, and AI certifications to advance your skills .Grow with the best - Learn from top engineers, data scientists, and AI experts in a dynamic, fast-moving workplace .Committed to ethical AI - Work in an environment where governance, transparency, and security are at the core of everything we build .Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the 140,000+ coders, tech shapers, and growth makers at Genpact and take your career in the only direction that matters: Up. Let's build tomorrow together.Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.