Senior Machine Learning Engineer (GenAI & Production ML Systems)

Description

Holisticon Insight is a data-focused technology and consulting company, part of the Nexer Group. Our mission is simple: We make companies Data Driven.

We build data platforms and data-intensive systems that solve real business problems. We work end-to-end, from integrating data from multiple sources (including IoT and operational systems), through building scalable data pipelines and semantic layers, to delivering analytics and AI solutions used in production.

Our projects often combine data engineering, cloud, and software development. We don’t just process data - we also build systems that generate it, such as IoT and digital platforms, which later become part of the data ecosystem. You’ll work on real use cases – optimizing processes, enabling better decisions, and building data products used by business teams. We focus on clean architecture, modern tech stacks, and ownership of what we build.

At Holisticon Insight we value strong engineering skills, autonomy, and collaboration. We keep a flat structure, small teams, and a lot of responsibility on the engineer level.

Check us out! 👉https://holisticon.pl/holisticon-insight/

We are looking for a Senior Machine Learning Engineer to join a strategic AI initiative focused on developing production-grade machine learning and generative AI systems for complex engineering and supply chain domains.

This role combines Generative AI, NLP, predictive modeling, and MLOps. You’ll work on solutions that transform unstructured documents and regulations into structured, actionable data, while also building predictive models supporting supply chain intelligence and decision-making processes.

You’ll collaborate closely with Data Scientist, Data Engineer, Backend Engineer, and domain experts to deliver scalable, secure, and explainable AI solutions operating in high-standard enterprise environments.

You’ll be involved in the full ML lifecycle – from experimentation and model development to deployment, optimization, and monitoring in production environments. We’re looking for someone who enjoys solving complex problems, building scalable AI systems, and collaborating closely with engineers, data specialists, and business stakeholders.

Your Responsibilities

• Design and develop production-grade Machine Learning and Generative AI solutions.
• Build and optimize NLP and LLM pipelines for document processing and requirements extraction.
• Develop RAG (Retrieval-Augmented Generation) systems and semantic search solutions.
• Create predictive models for forecasting, anomaly detection, and risk scoring.
• Implement prompt engineering strategies to improve LLM performance on domain-specific tasks.
• Design and maintain automated ML pipelines and model deployment workflows.
• Deploy and monitor ML models in secure production environments.
• Optimize model inference performance and scalability.
• Build preprocessing pipelines for both structured and unstructured data sources.
• Collaborate with Data Engineers, Data Scientists, Backend Engineers, and domain experts to deliver end-to-end AI solutions.
• Contribute to architectural decisions, engineering standards, and best practices across AI initiatives.

You might be the perfect match if you possess the following competencies:

• 5+ years of experience in Machine Learning Engineering with production-grade AI systems.
• Expert-level Python skills and strong knowledge of ML libraries such as PyTorch, TensorFlow, scikit-learn, Pandas, and NumPy.
• Hands-on experience with transformer architectures and LLMs (e.g. GPT, BERT, Llama).
• Experience building NLP and Generative AI solutions using frameworks such as Hugging Face and LangChain.
• Practical experience implementing RAG (Retrieval-Augmented Generation) architectures and semantic search systems.
• Experience with prompt engineering techniques and LLM optimization strategies.
• Strong understanding of predictive modeling, anomaly detection, and forecasting techniques.
• Experience deploying and maintaining ML systems in production environments.
• Practical knowledge of MLOps practices, including Docker, Kubernetes, MLflow, and automated ML pipelines.
• Experience designing data preprocessing pipelines for structured and unstructured data sources.
• Strong SQL and data processing skills.
• Solid understanding of model performance optimization, monitoring, and retraining strategies.
• Strong communication and collaboration skills.

Nice To Have

• Experience working in supply chain, engineering, defense, or other regulated industries.
• Experience with secure or on-premise AI deployment environments.
• Familiarity with optimization algorithms and decision-support systems.
• Experience working in Agile delivery models and structured engineering environments.
• Background in building explainable and auditable AI systems.

By Joining Holisticon Insight You Will Get

• Life insurance
• Multisport card
• Fully remote job
• Private medical care
• Flexible working hours
• Amazing integration events on a regular basis
• Training budget (e.g. Microsoft Azure Certifications)
• Opportunity to impact our company culture build-up
• Work equipment (laptop, 2 monitors, and accessories)