Machine Learning Ops Engineer Full-time

Our Company

Changing the world through digital experiences is what Adobe’s all about. We give everyone-from emerging artists to global brands-everything they need to design and deliver exceptional digital experiences! We’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen.

We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours!

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 Adobeproducts 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.

Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this position is $150,700 — $284,400 annually. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process.

At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission), and short-term incentives are in the form of sales commission plans. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP).

In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award.

Adobe is proud to be an Equal Employment Opportunity and affirmative action employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other applicable characteristics protected by law. Learn more.

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