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

Billennium; Polska; Hybrid; PLN 150,000 - 210,000; Full time

Benefits offered by this job

Udemy for Business

Private medical care

Multisport card

Language lessons

Shopping vouchers

Job summary

Billennium, a global technology company, seeks aSenior AI/ML Engineer to build and scale an enterprise MLOps platform powering real-time and batch ML workloads. You will design AI agents, orchestrate workflows, and ensure secure, scalable infrastructure in a highly regulated environment.

You will collaborate with Data Scientists, Platform Engineers, and Architects to deliver production-grade AI solutions, implement cloud-native MLOps, and advance agentic AI capabilities across the organization.

Qualifications

• Understanding of ML concepts and end-to-end model lifecycle.
• Understanding of Agentic AI concepts, AI agents, tool calling, RAG, workflow orchestration.

Responsibilities

• Design, develop, and deploy production-grade AI and ML solutions.
• Build AI agents and workflows that automate business processes.
• Create APIs and microservices exposing ML models and AI capabilities.
• Maintain ML training, inference, and orchestration pipelines.
• Collaborate with Data Scientists and stakeholders to translate requirements.

Skills

ML concepts

Agentic AI

Kubernetes

Docker

CI/CD

Cloud solutions

Security principles

Distributed systems

Tools

Kubernetes

Docker

LangChain

Kubeflow Pipelines

Job description

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 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.
• 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.
• Monitor, evaluate, and optimize AI and ML systems in production.
• Promote best practices around Generative AI and Agentic AI development.
• 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.
• Ensure platform reliability, security, governance, and observability.
• Troubleshoot production issues and improve platform performance.

Requirements

• Understanding of Machine Learning concepts and the end‑to‑end model lifecycle.
• Understanding of Agentic AI concepts, AI agents, tool calling, RAG, workflow orchestration, and retrieval‑based systems.

Software Engineering

• 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.
• Hands‑on experience with Kubernetes and Docker.
• Experience with ML systems.
• Experience building and operating MLOps platforms.
• Knowledge of CI/CD processes for ML and AI workloads.
• Experience with cloud solutions.
• Understanding of cloud‑native architecture and security principles.

Nice to Have

• Understanding of monitoring and observability for AI and ML systems.
• Proven experience deploying ML models into production environments.
• Experience with LangChain or similar AI orchestration frameworks.
• Experience building AI agents for business process automation.
• Experience with Kubeflow Pipelines.
• Experience working in regulated industries such as healthcare, life sciences, pharmaceutical, or financial services.

• 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.