Sr Machine Learning Ops Engineer

Senior ML Ops Engineer 

As a Machine Learning (Ops) Engineer you will be responsible for developing and maintaining the infrastructure required to deploy, monitor, and manage machine learning models efficiently and effectively. This role is critical in bridging the gap between research and engineering, ensuring that our AI solutions are scalable, reliable, and seamlessly integrated into our products. This role requires you to thrive in a fast-paced environment, be passionate about AI/ML, and be constantly looking for ways to optimize and automate machine learning workflows. 

Responsibilities 

• Pipeline Development: Build and maintain robust CI/CD pipelines for machine learning systems, enabling rapid iteration and delivery of AI features.  

• ML Model Deployment: Automate and streamline the deployment of machine learning models to production, ensuring they are scalable, secure, and efficient. 

• Performance Monitoring: Implement monitoring tools and processes to track the performance of machine learning models in production, identifying any issues or degradation over time. 

• Collaboration: Work closely with data scientists and engineers to ensure machine learning models are effectively integrated into Adobe products and systems. 

• Environment Management: Manage the ML development and production environments, ensuring they are optimized for performance and aligned with project requirements. 

• Tooling and Automation: Identify, evaluate, and implement tools and technologies to improve the efficiency and effectiveness of the machine learning lifecycle (Model evaluation, Feedback loops, A/B testing etc)  

• Best Practices: Advocate for and implement best practices in MLOps, ensuring high standards of quality, reliability, and performance across all AI initiatives. 

Qualifications: 

• Industry experience building end-to-end Machine Learning infrastructure with deep knowledge of modern cloud infrastructure including Kubernetes, Infrastructure as Code, AWS, and GCP. 

• Expertise in programming languages such as Python 

• Experience with Computer Vision models and GenAI technology including GAN, CLIP, Diffusion, MLLM, etc. 

• Experience with ML modeling frameworks (PyTorch, Tensorflow, ONNX, etc.), and model serving platform s (TorchServe, TensorFlow Serving, NVIDIA Triton inference server, etc.) 

• Familiarity with databases in general, VectorBD experience is a plus. 

• Experience with CI/CD tools (e.g., Jenkins, GitLab CI)  

• Strong problem-solving skills and the ability to work collaboratively across teams. 

• Excellent communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders. 

Candidate Profile: 

• Master in Computer Science  

• Proven experience of 10+ years in software engineering, with a focus on machine learning and MLOps for at least 6years, and a strong understanding of machine learning models and algorithms. 

• Track record of delivering cloud-scale, data-driven products, and services that are widely adopted with large customer bases. 

• Ability to lead a team while working autonomously.  

• An ability to think strategically, look around corners, and create a vision for the current quarter, the year, and five years down the road. 

• A relentless pursuit of great customer experiences and continuous improvements to the product.