Role Description This engagement is focused on building an internal AI platform that enables developers to ship AI-powered services efficiently. The objective is to improve DevEx and reduce time-to-market for AI features. - Build and operate the AI platform infrastructure enabling developers to ship LLM-based services faster. - Implement and maintain Kubernetes-based runtime environments (incl. AKS) for AI workloads. - Manage infrastructure as code with Terraform (modules, environments, CI/CD automation). - Support LLM workflows: RAG, agents, prompt experimentation, evaluations, and deployment patterns. - Integrate and operate tooling such as Azure AI Foundry, LiteLLM, Langfuse, MLflow. - Orchestrate pipelines using Kubeflow Pipelines and/or Argo Workflows (build, deploy, evaluate). - Improve platform reliability and observability (monitoring, logging, tracing, cost/perf signals). - Collaborate closely with developers to streamline DX (APIs, templates, docs, golden paths, automation). Qualifications - Strong hands-on experience with Kubernetes in production (preferably AKS). - Solid Terraform expertise (IaC best practices, multi-env setups). - Practical experience supporting ML/LLM workloads in a platform or DevOps/MLOps context. - Proficiency in Python for automation, scripting, and supporting APIs/evaluation tooling. - Understanding of CI/CD, release processes, and production-grade operations. - Ability to work under tight timelines and deliver pragmatically. Requirements - Experience building internal developer platforms or “paved roads” for engineering teams. - Familiarity with LLM evaluation frameworks, prompt testing workflows, and LLM observability. - Exposure to RAG architectures, vector databases, and agentic patterns. - Experience with Kubeflow, Argo, and ML lifecycle tooling. Engagement Type Long-term B2B contract. Team You will join a team of 5, with 3 AI Platform Engineers being added. Location / Timezone Remote work from Croatia, Poland, Portugal, and Serbia. European working hours. Occasionally available for meetings up to 10:00 AM PST (US overlap).

• Design and implement scalable, secure, and cost‑efficient MLOps solutions leveraging AWS and Databricks. • Automate ML deployment pipelines, reducing manual intervention and operational overhead. • Collaborate closely with data scientists to ensure solutions align with established MLOps architecture, best practices, and platform standards. • Integrate security controls and compliance requirements throughout the entire machine learning lifecycle. • Own and manage incidents end‑to‑end, from root cause analysis to prevention of future occurrences. • Contribute to software system architecture and the design of platform‑level components. • Build and optimize ML training, retraining, and inference pipelines, ensuring reliability and scalability. • Enhance observability with metrics, logging, tracing, and dashboards to ensure system visibility and performance. • Drive best practices in infrastructure automation, CI/CD, and cloud resource management across ML teams.

Innovexis is looking for a passionate and motivated Machine Learning Intern to join our innovative team in Bengaluru. This remote internship offers a unique opportunity to gain hands-on experience in the exciting field of education management through the application of machine learning technologies. As a Machine Learning Intern, you will assist in the development and implementation of machine learning models that enhance our educational platforms. You will collaborate with experienced professionals to work on real-world projects that aim to improve learning outcomes and optimize educational processes. This internship will provide you with invaluable skills and insights into the intersection of technology and education. We offer a competitive salary range of ₹20,000 - ₹25,000 per month, along with a supportive environment for personal and professional growth in the fast-evolving education sector. Responsibilities - Assist in the design and development of machine learning algorithms - Analyze datasets to extract meaningful insights - Collaborate with the data science team to implement models - Participate in research and development of new machine learning techniques - Test and validate machine learning models for accuracy and performance - Document processes and results for future reference - Stay updated on the latest trends in machine learning and education technology - Contribute to team meetings and brainstorming sessions Requirements - Currently pursuing or recently completed a degree in Computer Science, Data Science, or a related field - Basic understanding of machine learning concepts and algorithms - Familiarity with programming languages such as Python or R - Experience with data analysis and visualization tools - Strong analytical and problem-solving skills - Excellent communication and teamwork abilities - Ability to work independently in a remote environment - Enthusiasm for learning and applying new technologies

• Build the ML stack from the ground up • Detecting anomalies in API traffic • Own the full lifecycle • Design experiments and metrics • Work with text and structured behavioral data • Leverage LLMs where they add value • Shape the technical direction