Associate Machine Learning Engineer

Summary

Join Docplanner's global Machine Learning and Data Science unit as a Machine Learning Engineer. You will support a product area within the Noa organization, delivering end-to-end ML capabilities and working with cross-functional teams. Responsibilities include designing, deploying, and iterating on ML services for diverse data types, assessing and optimizing platform engineering and MLOps, researching and deploying LLM-powered solutions, and partnering with the AI Platform team. You will also architect and maintain data pipelines. The ideal candidate has at least one year of professional experience as an ML Engineer or Data Scientist in a fast-paced environment, expertise in production-grade MLOps, and proficiency in deep learning frameworks. Docplanner offers a competitive salary, share options, flexible work arrangements, comprehensive health benefits, and various other perks.

Requirements

• At least one year of professional experience as an ML Engineer or Data Scientist in a fast-paced, product-driven tech environment
• Demonstrated expertise in production-grade MLOps, leveraging, for example, orchestration with Kubernetes, model serving via FastAPI, NVIDIA Triton and KServe, Apache Airflow for data pipelines
• Good understanding and proficiency in deep learning frameworks such as PyTorch or TensorFlow
• Proven ability to integrate, deploy, and optimize large language models in production-grade industry environments, ensuring scalability and robust performance. Knowledgeable in prompt engineering, basis of agent‐based workflows, and the generation and manipulation of embeddings
• Problem-solving mindset and adaptability in dynamic environments with a focus on delivering business value to end customers
• Proven ability to manage timelines, prioritize tasks, and deliver results under tight deadlines
• Curiosity and eagerness to collaborate with cross-functional teams (e.g., product, marketing, engineering)

Responsibilities

• Work closely with cross-functional teams, including scientists, engineers, and product stakeholders, to deliver AI-driven machine learning initiatives that directly contribute business objectives
• Design, deploy and iterate over ML services for diverse data types (e.g., audio, text), while proactively identifying and eliminating performance bottlenecks driving continuous improvements
• Assess platform engineering and MLOps bottlenecks; research and design scalable GPU resource-optimization strategies, and recommend solutions that balance performance, cost, and reliability
• Research, architect, and deploy LLM-powered information retrieval solutions (eg. RAG) to deliver accurate and scalable results in complex, multilingual product environments
• Partner with the AI Platform team to refine MLOps best practices, evolve frameworks, and establish efficient, scalable workflows
• Architect, deploy, and maintain high-throughput, reliable data pipelines to support training-set curation and data-annotation tooling

Benefits

• A salary adequate to your experience and skills
• Share options plan after 6 months of working with us
• Remote or hybrid work model with or hub in Warsaw
• Flexible working hours (fully flexible, as in most cases you only have to be on a couple of meetings weekly)
• 26 days of paid time off (depending on your contract)
• Additional paid day off on your birthday or work anniversary (you choose what you want to celebrate)
• Private healthcare plan with Signal Iduna for you and subsidized for your family
• Multisport card co-financing for you to have access to sports facilities across Poland
• Access to iFeel , a technological platform for mental wellness offering online psychological support and counseling