Senior ML Engineer / MLOps Engineer

Billennium is a global technology company with over 20 years of experience, committed to innovation and empowering businesses. As an employer, we offer a supportive, growth-focused environment where collaboration and creativity thrive. Join us to shape the future of technology together! About the Role Join a team building and operating a large-scale MLOps platform that powers machine learning and AI solutions in a highly regulated environment. The platform enables Data Scientists and researchers to develop, train, deploy, and manage ML models at scale using cloud-native technologies. You will work on an ecosystem supporting hundreds of machine learning models running in both real-time and batch processing scenarios, with a strong focus on automation, scalability, security, and operational excellence. As the platform evolves toward Agentic AI, you will help design and deliver AI agents, LLM-powered applications, and intelligent automation solutions that streamline complex business processes and support decision-making at scale. This role combines software engineering, machine learning engineering, AI engineering, and platform engineering. You'll collaborate closely with Data Scientists, Platform Engineers, and Architects to deliver production-ready AI solutions and continuously enhance the organization's MLOps capabilities. What You Will Do AI & Machine Learning Engineering (50%) - Design, develop, and deploy production-grade AI and Machine Learning solutions. - Build AI agents and agentic workflows that automate business processes and support decision-making. - Develop LLM-powered applications and orchestrate multi-step AI workflows. - Create APIs and microservices exposing ML models and AI capabilities. - Design and maintain ML training, inference, and agent orchestration pipelines. - Collaborate with Data Scientists and business stakeholders to translate requirements into scalable technical solutions. - Integrate AI agents with enterprise platforms, data sources, and business applications. - Monitor, evaluate, and optimize AI and ML systems in production. - Promote best practices around Generative AI and Agentic AI development. MLOps & Platform Engineering (50%) - Build and maintain cloud-native MLOps and AI platforms. - Develop infrastructure supporting model serving, AI agents, and scalable inference workloads. - Manage Kubernetes-based environments and supporting cloud infrastructure. - Build and operate CI/CD pipelines for ML and AI deployments. - Implement Infrastructure as Code using Terraform or similar technologies. - Ensure platform reliability, security, governance, and observability. - Troubleshoot production issues and improve platform performance. - Contribute to platform architecture and technical roadmap discussions. Requirements AI & Machine Learning - Strong understanding of Machine Learning concepts and the end-to-end model lifecycle. - Hands-on experience with modern ML frameworks such as PyTorch or TensorFlow. - Proven experience deploying ML models into production environments. - Experience building AI-powered applications using modern LLM frameworks. - Understanding of Agentic AI concepts, AI agents, tool calling, RAG, workflow orchestration, and retrieval-based systems. - Ability to design end-to-end AI solutions addressing real business challenges. Software Engineering - Strong Python development skills. - Experience building production-grade APIs using FastAPI, Flask, or similar frameworks. - Solid software engineering and system design principles. - Experience with testing, version control, and CI/CD practices. - Ability to write maintainable, scalable, and production-ready code. MLOps & Platform Engineering - Hands-on experience with Kubernetes and Docker. - Experience with Kubeflow and ML pipeline orchestration. - Experience building and operating MLOps platforms. - Knowledge of CI/CD processes for ML and AI workloads. - Experience with Infrastructure as Code (Terraform or similar). - Understanding of monitoring and observability for AI and ML systems. Cloud Technologies - Strong experience with AWS, including services such as EKS, EC2, S3, and Lambda. - Experience with Azure or GCP is also welcomed. - Understanding of cloud-native architecture, networking, and security principles. Nice to Have - Experience with LangChain, LangGraph, LlamaIndex, or similar AI orchestration frameworks. - Experience building AI agents for business process automation. - Experience with RAG architectures and vector databases. - Experience with KServe and Kubeflow Pipelines (KFP). - Experience with Weights & Biases or comparable experimentation platforms. - Experience with LLM observability and evaluation frameworks. - Experience working in regulated industries such as healthcare, life sciences, pharmaceutical, or financial services. - AWS, CKA, or CKAD certifications. Benefits Comprehensive benefits - enjoy Udemy for Business, private medical care, Multisport card, veterinary package, language lessons, and shopping vouchers.Flexibility - adaptable working hours and remote/hybrid work options to suit your lifestyle & location.Career growth - access opportunities for professional development and learning, including perks related to our official partnerships with global IT giants: Microsoft, AWS, Snowflake, Salesforce & more.Global collaboration - work with a diverse, international team.Innovative environment - be part of a forward-thinking and growth-oriented workplace.Engaging community – Work with passionate professionals and participate in team-building events, hackathons, and CSR initiatives to make an impact beyond work.Team-building events including our company tradition (annual company event in Mazury).A pleasant surprise to start your journey with us in the form of a welcome pack.