Job
Description
Job Summary In this role, you will lead the architecture and implementation of MLOps/LLMOps systems within OpenShift AI. Job Description Company Overview: Outsourced is a leading ISO certified India & Philippines offshore outsourcing company that provides dedicated remote staff to some of the world's leading international companies. Outsourced is recognized as one of the Best Places to Work and has achieved Great Place to Work Certification. We are committed to providing a positive and supportive work environment where all staff can thrive. As an Outsourced staff member, you will enjoy a fun and friendly working environment, competitive salaries, opportunities for growth and development, work-life balance, and the chance to share your passion with a team of over 1000 talented professionals. Job Responsibilities Lead the architecture and implementation of MLOps/LLMOps systems within OpenShift AI, establishing best practices for scalability, reliability, and maintainability while actively contributing to relevant open source communitiesDesign and develop robust, production-grade features focused on AI trustworthiness, including model monitoringDrive technical decision-making around system architecture, technology selection, and implementation strategies for key MLOps components, with a focus on open source technologiesDefine and implement technical standards for model deployment, monitoring, and validation pipelines, while mentoring team members on MLOps best practices and engineering excellenceCollaborate with product management to translate customer requirements into technical specifications, architect solutions that address scalability and performance challenges, and provide technical leadership in customer-facing discussionsLead code reviews, architectural reviews, and technical documentation efforts to ensure high code quality and maintainable systems across distributed engineering teamsIdentify and resolve complex technical challenges in production environments, particularly around model serving, scaling, and reliability in enterprise Kubernetes deploymentsPartner with cross-functional teams to establish technical roadmaps, evaluate build-vs-buy decisions, and ensure alignment between engineering capabilities and product visionProvide technical mentorship to team members, including code review feedback, architecture guidance, and career development support while fostering a culture of engineering excellence Required Qualifications 5+ years of software engineering experience, with at least 4 years focusing on ML/AI systems in production environmentsStrong expertise in Python, with demonstrated experience building and deploying production ML systemsDeep understanding of Kubernetes and container orchestration, particularly in ML workload contextsExtensive experience with MLOps tools and frameworks (e.g., KServe, Kubeflow, MLflow, or similar)Track record of technical leadership in open source projects, including significant contributions and community engagementProven experience architecting and implementing large-scale distributed systemsStrong background in software engineering best practices, including CI/CD, testing, and monitoringExperience mentoring engineers and driving technical decisions in a team environment Preferred Qualifications Experience with Red Hat OpenShift or similar enterprise Kubernetes platformsContributions to ML/AI open source projects, particularly in the MLOps/GitOps spaceBackground in implementing ML model monitoringExperience with LLM operations and deployment at scalePublic speaking experience at technical conferencesAdvanced degree in Computer Science, Machine Learning, or related fieldExperience working with distributed engineering teams across multiple time zones What we Offer Health Insurance: We provide medical coverage up to 20 lakh per annum, which covers you, your spouse, and a set of parents. This is available after one month of successful engagement.Professional Development: You'll have access to a monthly upskill allowance of ₹5000 for continued education and certifications to support your career growth.Leave Policy: Vacation Leave (VL): 10 days per year, available after probation. You can carry over or encash up to 5 unused days.Casual Leave (CL): 8 days per year for personal needs or emergencies, available from day one.Sick Leave: 12 days per year, available after probation.Flexible Work Hours or Remote Work Opportunities – Depending on the role and project.Outsourced Benefits such as Paternity Leave, Maternity Leave, etc.
