Machine Learning Operations Engineer

We're a fully female-founded company on a mission to change the way people search and shop online for fashion...forever! We're going to spark a new era of fashion discovery, igniting confidence in everybody and every body, and to create a world where fashion confidence starts with "us". We are at the beginning of an exciting journey and we're looking for top talent to join our team. Unlike many start-ups we're well funded, have a detailed business and financial plan, and are looking for experienced, passionate professionals to join us in creating and scaling a game-changing business. So if you want a role where you will make a major impact and want to be a part of a team of women building an incredible product and experience for other women, come join us and make the most move of your career! About the Role We're looking for an experienced ML (Machine Learning) Ops Engineer to design, build and scale the infrastructure on which we deploy our ML models. This role is perfect for someone who thrives on building scalable, high-performance systems and reliable backend services. You'll work closely with data science and engineering to deploy and integrate our model into business applications, APIs and micro services. You'll also be directly responsible for monitoring and logging, ensuring security and compliance, and optimising performance of the environment. Key Responsibilities Model Deployment & Serving: Design, build, and maintain scalable infrastructure to deploy ML models developed by the Data Science team into production. Provisioning Cloud Resources: Automating the setup and management of scalable, repeatable, and secure cloud infrastructure (AWS) using Terraform and Infrastructure as Code (IaC) best practices CI/CD & Automation: Implement CI/CD pipelines to automate model deployment, working with engineering to align on existing practices. Backend Integration: Work with engineering teams to integrate ML models into business applications, APIs, and microservices. Monitoring & Logging: Set up robust monitoring, logging, and alerting for the implemented services, model performance, and system reliability. Data Engineering Support: Collaborate on data pipelines and ETL processes. Security & Compliance: Ensure ML infrastructure is secure, follows best practices, and adheres to compliance regulations Performance Optimisation: Optimise resource utilisation and reduce latency Experience & Qualifications Experience: 3+ years in MLOps, DevOps, or Cloud Engineering with a focus on ML model deployment Cloud Platforms: AWS including services like Sagemaker, Lambdas, S3, EC2, ECS, Fargate, RDS, MongoDB, Cloudwatch Programming skills: Strong coding ability in Python and Bash CI/CD & Automation: Github Actions, Github CI/CD Observability: Experience and familiarity with observability tools ML Frameworks: Understanding of TensorFlow, PyTorch, OpenAI, HuggingFace ML Areas: experience working with solutions within LLM and computer vision Collaboration: Ability to work closely with Data Scientists, Engineers, and Software Engineers Work Schedule As the client is UK-based, you will be required to work in UK daytime: Monday to Friday 14:00 - 23:00 IST (08:30 am - 17:30 GMT)

We're a fully female-founded company on a mission to change the way people search and shop online for fashion...forever! We're going to spark a new era of fashion discovery, igniting confidence in everybody and every body, and to create a world where fashion confidence starts with "us". We are at the beginning of an exciting journey and we're looking for top talent to join our team. Unlike many start-ups we're well funded, have a detailed business and financial plan, and are looking for experienced, passionate professionals to join us in creating and scaling a game-changing business.