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.