Senior ML Engineer / MLOps Engineer (Agentic AI & Cloud Platforms)

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.