MLOps Engineer

MLOps Engineer Position at Evolution

About the company:

At Evolution, we’re building AI that builds AI (AI-for-AI). Our platform, Earth, autonomously designs and improves AI systems. It’s powered by a cutting-edge fusion of modernized evolutionary algorithms (genetic algorithms) and state-of-the-art AI techniques, purpose-built for today’s most demanding challenges in ML and AI.

What makes Evolution unique?

Evolution operates across a wide spectrum of AI domains — including prediction, LLMs, computer vision, signal processing, generative AI, complex planning, real-time control, and more. This breadth allows for a dynamic and intellectually stimulating environment, where each project brings new scientific challenges and opportunities. No two days are the same, and team members regularly engage with a variety of methods, tools, and problem spaces.

Job description:

As an MLOps Engineer at Evolution, you’ll be responsible for advancing the infrastructure, tooling, and operational backbone that power our AI-for-AI platform, Earth, as well as multidisciplinary real-world, high-impact data science implementations. This role sits at the intersection of software engineering, cloud architecture, and ML/AI. You’ll be working with a team of brilliant and experienced data scientists, and working closely with product and business stakeholders to align goals and priorities. You will take ownership of designing and maintaining scalable, production-grade systems that enable rapid experimentation, seamless deployment, and robust execution of advanced AI workflows. This position will require undergoing a security clearance process.

What you’ll do:

• Contribute to the evolution of our own AI-for-AI platform (Earth) by developing new capabilities, optimizing execution flows, and building tooling that accelerates research.
• Foster a fast-paced, Agile development culture and contribute to the product roadmap.
• Collaborate with product and business teams to align on goals and KPIs.
• Engage directly with clients: from translating business needs to providing support.
• Deploy, integrate and monitor production-level data and ML pipelines.
• Design and implement cloud-native architectures on AWS, ensuring scalability, robustness, and cost-efficiency.
• Build and maintain containerized services using Docker and Kubernetes, including cluster-level orchestration and automation.
• Develop backend and infra services using Python and FastAPI, with clean, maintainable, and production-grade code.
• Manage and model data across S3, SQL, and NoSQL systems; implement efficient ODM/ORM-based storage flows (Beanie or equivalent).
• Implement event-driven and scheduled workflows using Lambda, Step Functions, EventBridge, or similar orchestration tools.
• Enable data-science teams with reproducible environments, infrastructure abstractions, and seamless integration with backend services.
• Improve reliability and observability across pipelines and services using logging, monitoring, and alerting best practices.

Mandatory requirements:

• BSc / BA degree in Computer Science or Software Engineering.
• 3+ years of hands-on experience with Python, including writing maintainable and production-grade code.
• Practical experience with Docker for containerization and Kubernetes for orchestration in production environments.
• Strong practical knowledge of AWS cloud services.
• Hands-on experience building and supporting production data/ML pipelines, including: Interaction with S3 datasets; Orchestrating flows using Lambda, Step Functions and EventBridge; Managing scheduled or event-driven processes.
• Proven experience building and maintaining services using FastAPI.
• Strong familiarity with Beanie (or similar ODMs) for data modeling and persistence.
• Experience with SQL and NoSQL databases, designing schemas, queries, and performance tuning.
• Ability to support data science teams with infrastructure, reproducible environments, and integration with backend services.

Advantage:

• MSc / MA degree in Computer Science or Software Engineering.
• Experience with CI/CD tools and workflows (GitHub Actions, GitLab CI, CodePipeline).
• Experience implementing task orchestration or background processing using TaskIQ (or similar frameworks).
• Strong knowledge of asynchronous programming and event-driven service design.
• Native-level English or strong command of written and spoken English.
• Demonstrated strength in technical writing and documentation.

Job location:

Our office is located in the Bursa district of Ramat-Gan, right next to Israel Railways and the Light Rail. This is a primarily on-site role, with most work done from the office.