DevJobs

MLOps Engineer

Overview
Skills
  • Python Python ꞏ 3y
  • SQL SQL
  • NoSQL NoSQL
  • GitHub Actions GitHub Actions
  • CI/CD CI/CD
  • AWS AWS
  • Docker Docker
  • Kubernetes Kubernetes
  • Beanie
  • EventBridge
  • FastAPI
  • Lambda
  • S3
  • Step Functions
  • TaskIQ
  • asynchronous programming
  • CodePipeline
  • event-driven service design
  • GitLab CI

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.

Evolution.inc