Work experience
Machine Learning Engineer and Consultant (remote)
October 2023 – present
Company name: Self-employed
Key points:
- Self-employed ML engineer and consultant solving real-world business problems through the right ML approaches: whether classical algorithms or modern deep learning.
- Operates across the full spectrum: from low-level ML engineering to AI strategy and business alignment.
- Clients include GoodAI (AI People – an LLM-powered game, see demo) and other AI consulting and ML engineering engagements.
- Experience spans NLP, computer vision, traditional ML, and speech systems (TTS/ASR).
- Capable of handling full pipeline (MLOps, backend, deployment) when needed.
- Delivered lectures at AI Center Lipik (AI Centar Lipik), educating future AI developers.
Job description:
As a self-employed machine learning engineer and consultant, I solve business problems by selecting and implementing the right ML approaches for each use case. My work spans from hands-on ML engineering (training models and writing production code) to strategic consulting where I assess AI feasibility, define roadmaps, and align technical solutions with business objectives. At GoodAI, I contributed to AI People (an LLM-powered game) by fine-tuning and deploying LLMs locally, engineering prompts and safety systems, implementing TTS/ASR capabilities, and maintaining cloud infrastructure. Beyond hands-on work, I’ve worked directly with company leadership (CEOs/CTOs) to align technical solutions with business objectives and define AI implementation roadmaps. When projects require it, I handle the full pipeline including MLOps, backend development, and deployment, though my core strength lies in AI consulting and ML models development. While currently focused on NLP and GenAI, I remain open to diverse ML challenges across domains.
Machine Learning Engineer (remote)
October 2020 – September 2023
Company name: TIS Group
Key points:
- Developed ML systems in computer vision and NLP, including a healthcare solution (SENDD) for early detection of neurological deviations in infants.
- Led end-to-end development of Vineyard Angel – a drone imagery analysis system for vineyard health assessment and missing plant detection.
- Built ML pipelines and contributed to deployment efforts using Python (PyTorch, scikit-learn, OpenCV) on Microsoft Azure with Linux-based infrastructure.
- Participated in hackathons: built a scoliosis severity estimation system and CatAIog – LLM-based PDF document chatbot.
- Presented the Vineyard Angel project at the AI2FUTURE 2022 conference in collaboration with an agricultural partner.
Job description:
At TIS Group, I worked as a machine learning engineer across multiple projects, primarily in computer vision and natural language processing. One of the key projects was SENDD, a healthcare solution for early detection of neurological deviations in infants. I contributed across most of the ML pipeline, focusing on data science and model development, while supporting deployment efforts led by a teammate. The tech stack included Python (pandas, scikit-learn, TensorFlow, PyTorch), Jupyter, and Azure-based virtual machines running on Linux with Docker. We applied both classical (e.g., k-NN, SVM) and deep learning models (e.g., CNNs, autoencoders), and incorporated NVIDIA open-source technology in parts of the system. I also led the development of Vineyard Angel, a drone imagery analysis system that estimates missing vine plants and assesses canopy vigor. I handled everything from initial design to production deployment and later presented the project at the AI2FUTURE 2022 conference alongside our agricultural partner. In addition, I participated in hackathons where I led the development of a scoliosis severity estimation model and collaborated on building an LLM-powered chatbot that answers questions from PDF documents. I also created and voiced the video presentations for both solutions.
Software Engineer
July 2019 – February 2020
Company name: Rimac Automobili
Key points:
- Developed infrastructure for autonomous driving systems, ensuring synchronization and health checks of vehicle sensors and camera inputs.
- Processed raw radar and sensor data in real-time using low-level C++ code.
- Collaborated with senior engineers to integrate systems into the vehicle’s software stack.
- Utilized NVIDIA technologies and Git for development and version control.
- Balanced full-time and part-time responsibilities alongside university studies.
Job description:
At Rimac Automobili, I worked on the autonomous driving team, focusing on system infrastructure rather than direct machine learning development. My main responsibility was building and maintaining systems that ensured the synchronization and health of all onboard sensors, including cameras and radars. This involved real-time data processing and implementing logic to handle delays, missing frames, or timestamp mismatches. I worked extensively with low-level C++ code, integrating raw sensor data into the vehicle’s software stack. My work also involved using NVIDIA technologies and maintaining code via Git. I collaborated closely with senior engineers throughout the process. This role was a mix of full-time and part-time engagement, depending on my university schedule.
Unity C# Software Engineer
June 2016 – July 2016
Company name: COBE (Creators Of Beautiful Experiences)
Key points:
- Developed UI features in Unity using C# during a student engagement.
- Collaborated with a senior developer to align implementation with functional and design specifications.
- Contributed production-ready code and improved UI integration within an existing system.
Job description:
While still a university student, I worked as a freelance developer at COBE (Creators Of Beautiful Experiences). My main responsibility was building and integrating user interface components in Unity using C#. I contributed to an existing codebase, ensuring smooth integration of the UI with the system’s functional core. Working under the supervision of a senior developer, I helped align the implementation with both design and functional specifications. This project was one of my first professional experiences in software development during my studies.
Skills and tools
Proficient in
- Programming Languages: Python
- ML libraries: FastAPI, Hugging Face, NumPy, OpenCV, pandas, PyTorch, scikit-learn
- Tools: Azure, Git, Jupyter, Linux
- Domains: Computer Vision, GenAI, LLMs, NLP, Traditional ML
Familiar with
- Programming Languages: C++, SQL
- ML libraries: Django, Keras, PyInstaller, SciPy, TensorFlow
- Tools: AWS, CI/CD pipelines, Docker, GCP, Terraform, W&B
- Databases: Chroma, CosmosDB, PostgreSQL
- Domains: Agentic AI, ASR, Data Science, RAG, TTS