About Saarthee:Saarthee is a Global Strategy, Analytics, Technology and AI consulting company, where our passion for helping others fuels our approach and our products and solutions. Our diverse and global team work with one objective in mind: Our Customers’ Success. At Saarthee, we are passionate about guiding organizations towards insights fueled success. That’s why we call ourselves Saarthee–inspired by the Sanskrit word ‘Saarthi’, which means charioteer, trusted guide, or companion. Cofounded in 2015 by Mrinal Prasad and Shikha Miglani, Saarthee already encompasses all the components of Data Analytics consulting. Saarthee is based out of Philadelphia, USA with office in UK and India.Position Summary:We are seeking a skilled ML/DevOps Engineer to support and enhance our machine learning operations infrastructure. In this role, you will be responsible for monitoring production services, troubleshooting issues, and collaborating with teams to improve automation and system reliability. You will play a critical role in ensuring seamless model deployment, performance, and integration within our ML platformKey Responsibilities:Design and execute ML model load tests, create and automate end-to-end (E2E) test cases for individual models.Evaluate model scalability and latency by running metric suites under varying RPS (Request Per Second) to ensure smooth model rollouts.Enhance monitoring of model scalability and handle incidents related to increased error rates.Collaborate closely with machine learning engineers, backend engineers & QA test engineers across cross functional teams.Design, implement and maintain end-to-end CI/CD pipelines using Git, GitHub Actions, GitLab and Jenkins.Manage & optimize cloud infrastructure on AWS using Terraform, Docker and Kubernetes. Work with custom ML platforms, feature stores and ML monitoring tools.Apply best practices in machine learning and software engineering production deployments.Required Skills & Qualifications:Advanced Degree (PhD or Master’s) in computer science, Engineering, Statistics, or a related field.Minimum 4+ years of industry experience (research group/ R&D experience excluded).Strong machine learning, statistical and analytical skills.Hands om experience with Databricks, mlFlow and Seldon.Experience with Kubeflow, Tecton and Jenkins.Strong programming skills in Java, Python or Scala.Expertise in recommendation systems.Expertise in building and monitoring large scale, customer facing ML applications.Familiarity with feature store concepts and ML model monitoring practicesMandatory Skills : Python and Shell Scripting Terraform (Infrastructure as Code)AWS Cloud ServicesDocker and Kubernetes.What We Offer:Bootstrapped and financially stable with high pre-money evaluation.Above industry remunerations.Additional compensation tied to Renewal and Pilot Project Execution.Additional lucrative business development compensation.Firm building opportunities that offer stage for holistic professional development, growth, and branding.Empathetic, excellence and result driven organization. Believes in mentoring and growing a team with constant emphasis on learning.
Job Title
Machine Learning Engineer - MLOps