10/10/2026 updated

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AI & ML Engineer and Consultant | LLMs, Agentic AI, NLP, Computer Vision | Python, PyTorch

Vinkovci, Croatia
Only remote
M.Sc. in Computer Science, B.Sc. in Informatics (University of Zagreb)
Vinkovci, Croatia
Only remote
M.Sc. in Computer Science, B.Sc. in Informatics (University of Zagreb)

Profile attachments

CV - Mislav Jurić.pdf

About me

AI & ML Engineer and Consultant based in Croatia, working remotely. I help companies find out whether AI makes sense for their problem before they invest heavily, then build it. Outside work: family, friends, the gym and the occasional karaoke.

Application Programming Interfaces (APIs)Artificial IntelligenceComputer VisionC++ (Programming Language)ConsultingLinuxDocument RetrievalPython (Programming Language)PostgreSQLMachine LearningNatural Language ProcessingNumPyOpenCVTensorFlowAzure Machine LearningSciPyDocker ContainerGoogle CloudFeature EngineeringData SciencePyTorchLarge Language ModelsDeep LearningGenerative AIJupyterKerasGitLabGitFastAPIpandasScikit LearnHuggingFaceCosmos DBSpacyTerraformNatural Language UnderstandingDockerNatural Language GenerationJenkins
I'm an AI & ML engineer and consultant with 5+ years in machine learning. I help companies decide whether AI makes sense for their business problem before they invest heavily, and when it does, I take the work from feasibility assessment through working prototypes to production-ready models. Sometimes that means classical ML instead of deep learning; sometimes it means recommending against AI entirely.

What I do:
  • AI consulting: feasibility assessments, technical architecture, roadmaps and realistic timelines, working directly with CEOs and technical leaders
  • Technical leadership (e.g. AI Lead) or hands-on individual contribution within existing teams
  • End-to-end ML engineering: dataset design, model training and fine-tuning, optimization, and integration into production systems
  • API development, containerization and deployment when needed - on my own for smaller projects, or with engineering teams for larger systems

Selected results:
  • Cut BERT-based model inference time by roughly 50% with encoder layer pruning, across production and training frameworks
  • Raised the time needed to extract an LLM game's system prompt from under 1 minute to roughly 30 minutes for technical testers, and to days for non-technical QA
  • Fine-tuned local 7B LLMs (Llama, Mistral) with QLoRA, and found an NVIDIA In-Game Inferencing (NVIGI) SDK bug that NVIDIA later patched
  • Delivered a bug triage and root cause analysis agent proof of concept, chaining an Atlassian Rovo agent into a GitHub Copilot agent
  • Extended a Google Gemini Enterprise chatbot with custom Gmail and Google Drive integrations
  • As AI Lead on a computer vision project, caught that the edge hardware could not run the AI pipeline before development committed to it, and built the first end-to-end ML pipeline
  • Reduced pose-estimation training time from weeks to days by moving training to GPU and multi-GPU

Technical skills:
  • Domains: GenAI, LLMs, Agentic AI, RAG, NLP, Computer Vision, Traditional ML, ASR, TTS, Data Science
  • Languages: Python, C++, SQL
  • Frameworks & libraries: PyTorch, Hugging Face, scikit-learn, FastAPI, NumPy, pandas, OpenCV, spaCy, FlairNLP, LlamaIndex, SciPy, TensorFlow, Keras, Streamlit, PyInstaller
  • Cloud & tools: Azure, GCP, Vertex AI (incl. ADK), Docker, Terraform, Git, Jenkins, CI/CD pipelines, Linux, Jupyter, W&B, GNU Make, Prodigy
  • Databases: PostgreSQL, CosmosDB, Chroma

Industries I've worked in: healthcare, agriculture, gaming, automotive and advertising. I've also delivered lectures at AI Center Lipik and co-authored research papers on AI safety and applied machine learning.

I work remote-first and prefer honest conversations about constraints over optimistic promises.

Experience

Professional experience5 - 10 years
Freelancer since2023

Languages

EnglishFluentCroatianNative speaker

Project history

Senior Machine Learning Engineer

Newfire Global Partners

Internet & IT

  • Reduced BERT-based model inference time by roughly 50% by implementing an encoder layer-pruning technique across the production and model training frameworks
  • Built an NLP model end-to-end, designing the dataset via entity prelabeling and LLM-assisted labeling, training it, and integrating it into production to power a new feature that flags abnormal records
  • Retrained multiple NLP models under strict validation standards, running differential testing to verify performance before release
  • Developed new features and maintained production NLP pipelines within a 7+ year-old spaCy codebase, using an in-house FlairNLP-based framework for model training, and updated Jenkins CI/CD
Technologies: Python, NLP, BERT, spaCy, FlairNLP, LLM-assisted labeling, Jenkins, CI/CD

AI & ML Engineer and Consultant (remote)

Self-employed

Internet & IT

< 10 team member

Independent AI & ML engineer and consultant. I take on hands-on engineering - training AI/ML models, writing production code, designing and deploying pipelines to production - and the work that comes earlier: assessing whether AI is the right tool at all, shaping architecture, and setting timelines that survive contact with reality.

Engagements (listed separately below; some clients are under NDA and described by engagement type):
  • Senior AI Engineer - Bug Triage & Root Cause Analysis Agent (Confidential Client, 2026)
  • Senior AI Engineer - Enterprise Chatbot on Google Gemini (Confidential Client, 2026)
  • Senior Machine Learning Engineer - Newfire Global Partners (2025 - present)
  • AI Lead - Computer Vision Advertising Project (Confidential Client, 2025)
  • Machine Learning Engineer - AI People, LLM-powered game (GoodAI, 2023 - 2025)
Beyond client work:
  • Delivered lectures at AI Center Lipik, helping train the next generation of AI developers in Croatia
  • Gave an invited public talk on preserving cultural heritage in the age of AI

Senior AI Engineer - Bug Triage & Root Cause Analysis Agent

Confidential Client

Internet & IT

  • Delivered a functional proof-of-concept bug triage and root cause analysis pipeline, chaining a no-code Atlassian Rovo agent into a prompt-driven GitHub Copilot agent to surface likely root causes from bug reports and shorten manual triage
  • Designed an alternative system architecture in response to revised client IT policy, making development of the agent feasible
  • Partnered directly with stakeholders to gather requirements and demo iterations, and received IT policy updates directly from the downstream end client
Technologies: Agentic AI, LLMs, Atlassian Rovo, GitHub Copilot, prompt engineering

Senior AI Engineer - Enterprise Chatbot on Google Gemini

Confidential Client

Internet & IT

  • Extended a Google Gemini Enterprise chatbot with custom integrations beyond the platform's built-in connectors, enabling the agent to apply labels to emails in Gmail and move files in Google Drive
  • Evaluated the platform's no-code and high-code capabilities and partnered with stakeholders to scope feasible features aligned with their needs
Technologies: Google Gemini Enterprise, Vertex AI (incl. ADK), GCP, Agentic AI, LLMs, Python

AI Lead - Computer Vision Advertising Project

Confidential Client

Internet & IT

Took over technical leadership of a computer vision project after the previous AI lead left, starting with no roadmap, no dataset and no validated hardware.
  • Defined the technical architecture and established realistic delivery timelines with the CEO, tech lead, and infrastructure lead
  • Wrote the AI roadmap, a data annotation guide and a hardware validation report
  • Identified that the existing edge hardware could not run the AI pipeline, prompting a hardware change before development committed to an unworkable target
  • Built the project's first complete ML processing pipeline, running all features end-to-end where the previous prototype could not, and establishing a working baseline the incoming AI Lead reused
  • Mentored and managed a university-level engineer, assigning work, providing technical direction and code review
  • Took part in hiring the incoming AI Lead and left full documentation for continuity
Technologies: Computer Vision, Python, PyTorch, OpenCV, edge hardware

Machine Learning Engineer - AI People (LLM-powered game)

GoodAI

Internet & IT

  • Engineered prompt-protection mechanisms that increased time-to-extract the system prompt from under 1 minute to roughly 30 minutes for technical testers, and to days for non-technical QA
  • Contributed to a QLoRA training framework, adding OpenAI fine-tuning support, then inherited and used it to fine-tune local 7B LLMs (Llama, Mistral) after the lead departed
  • Ran and evaluated local LLM and ASR inference using llama.cpp, whisper.cpp, and NVIDIA In-Game Inferencing (NVIGI), identifying an SDK bug that NVIDIA later patched
  • Integrated local and cloud ASR/TTS, implementing a self-contained FastAPI + PyInstaller deployment for a local TTS model released under a week prior, and generated arbitrary synthetic voices by manipulating voice embeddings in vector space
  • Built content-filtering and safety mechanisms plus credit-calculation logic reconciling in-game credits against actual LLM, ASR, and TTS spend, surfacing a billing discrepancy
  • Helped deliver the alpha release to real players
Technologies: LLMs, QLoRA, Llama, Mistral, llama.cpp, whisper.cpp, ASR, TTS, FastAPI, PyInstaller, Python

Machine Learning Engineer (remote)

TIS Group

Internet & IT

50-250 team member

My first full-time ML role, spanning healthcare and agriculture - from model training and optimization on SENDD to owning a pipeline end-to-end on Vineyard Angel.
  • SENDD (healthcare): Reduced pose-estimation model training time from weeks to days by moving training onto GPU, and later multi-GPU, using NVIDIA's trt_pose
  • Improved pose-estimation accuracy through transfer learning and built a heatmap-feature classifier using kNN and SVM with PCA for dimensionality reduction
  • Vineyard Angel (agriculture): Led development of a drone-imagery pipeline from design to deployment, segmenting vineyard rows and gaps and estimating vine-gap counts with PyTorch Segmentation Models and OpenCV
  • Automated the pipeline on Azure via systemd-orchestrated VMs, and presented the project with the agricultural partner at AI2FUTURE 2022
  • Hackathons: built a scoliosis severity estimation system, and, with a team, an LLM-based chatbot over PDF documents
Technologies: Python, PyTorch, OpenCV, scikit-learn, Computer Vision, Azure, Linux

Software Engineering Intern

Rimac Automobili

Automotive & Vehicle Manufacturing

250-500 team member

  • Built C++ infrastructure around ML models within an autonomous-driving team, including systems parsing low-level radar message bytes
  • Worked with Linux, Git, and NVIDIA autonomous-driving hardware under the mentorship of a senior engineer
Technologies: C++, Linux, Git, NVIDIA autonomous-driving hardware

Certificates

iSAQB Certified Software Architect (CPSA-F)

iSAQB (examination by Certible)

2026

Docker Fundamentals

Adrian Cantrill (learn.cantrill.io)

2025

Generative AI with Large Language Models

DeepLearning.AI and AWS

2024

DeepLearning.AI TensorFlow Developer

DeepLearning.AI

2020

Portfolio

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