Jobs ML / AI

Senior AI Engineer needed to design and ship AI products for a healthcare company that enables remote patient monitoring, clinical research, and personalized healthcare. You'll build generative-AI workflows, clinical decision support, agents, and retrieval over health data — along with the evaluation and guardrails that make them safe to use in a clinical setting. You'll own these products end to end and work across teams, partnering closely with clinicians, product, and engineering to identify where AI genuinely improves a patient or clinician outcome — and explaining the trade-offs clearly to both technical and non-technical people. This is a hands-on senior role for an AI builder with strong software fundamentals who wants to own the outcome of an AI product, not just the code.

What You'll Do:

• Take AI products from problem framing to production — scope the use case, choose the approach (generative AI, classical ML, retrieval, agents, or a hybrid), and ship it
• Design prompts, tools, and retrieval strategies that work reliably in a clinical context, with structured outputs and clear failure modes
• Build the services and APIs that expose AI capabilities to our products, with real attention to latency, cost, and observability
• Shape the data behind each product — sources, schemas, labelling, and quality checks — and build the pipelines that prepare it for training, evaluation, and inference
• Define how quality is measured (offline metrics, golden sets, human review, and live monitoring) and use the results to drive iteration
• Build guardrails, content checks, and graceful degradation paths suited to healthcare use cases
• Operate AI products in production — monitor model behaviour, catch drift and regressions, and run incident response when needed
• Write production-quality code, tests, and documentation, review others' work to the same standard, and use AI-assisted development tools to move faster without compromising quality
• Partner with clinical, product, and engineering colleagues to decide where AI is — and isn't — the right answer, keeping everyone aligned and clearly communicating AI trade-offs to technical and non-technical stakeholders

• Mentor other engineers on applied AI — evaluation, generative-AI design patterns, and shipping models responsibly

   

What We're Looking For:

• 5+ years of professional software engineering experience, with meaningful time building and shipping AI/ML products in production
• A track record of owning an AI product from problem statement to launch — including model/approach selection, evaluation, and iteration based on real usage
• Hands-on experience with generative-AI systems: prompting, tool/function calling, retrieval-augmented generation (RAG), multi-step agents, structured output, and handling failure modes
• Solid grounding in core machine learning (supervised learning, embeddings, evaluation, overfitting, data quality), with the judgment to know when to use classical ML, fine-tuning, or off-the-shelf models — and when AI isn't the answer at all
• Strong production engineering skills — clean, well-tested code, sensible API design, and the ability to operate your own services (Python is our default)
• Comfort with the data side of an AI product — ingesting, cleaning, and modelling structured and unstructured data, and designing pipelines for training, evaluation, and inference
• An evaluation mindset — defining offline and online metrics, building golden sets or human-review loops, and catching regressions before users do
• Clear, confident written and verbal communication — you can explain AI trade-offs to an engineering stand-up and to a clinical or executive stakeholder in the same day, and adapt your style to each
• An ownership and product mindset — you care whether the model and the product are doing the right thing for users, you stay accountable after launch, and you balance capability, cost, latency, safety, and complexity for the stage of the product
• Confident with Git, code review, automated testing, and CI/CD

Nice to Have:

• Production experience with vector databases, embedding pipelines, and retrieval-quality tuning
• MLOps practices — model versioning, evaluation harnesses, shadow deployments, and prompt/dataset management
• Experience with cloud AI platforms (Azure AI, AWS Bedrock/SageMaker, GCP Vertex) and deploying inference on AWS, GCP, or Azure
• Familiarity with fine-tuning, distillation, or hosting open-weight models when economics or privacy call for it
• Background in healthcare, life sciences, or another regulated, data-sensitive domain (HIPAA, GDPR, ISO 27001, medical-device software)
• Experience with FHIR, HL7, or other healthcare interoperability standards

What Success Looks Like:

• AI products that ship and make a measurable difference — adoption, task completion, and clinical or operational outcomes where defined
• Healthy AI behaviour in production — strong evaluation scores, a high regression catch rate, and safety incidents avoided
• Reliable, observable AI services with healthy uptime, latency, and cost for the surfaces you own
• Predictable delivery within agreed scope and timelines
• Engineers you mentor or pair with growing and becoming more effective

On behalf of our client, we are looking for a Senior AI Engineer

Requirements:

- 5+ years of experience in AI Engineering, Data Engineering, or Applied ML Infrastructure

- Expert-level Python

- Strong experience with distributed processing frameworks (Apache Beam preferred; Spark/Flink acceptable)

- Hands-on experience integrating LLMs in production (prompting, orchestration, provider abstraction)

- Experience with graph databases (Dgraph, Neo4j, JanusGraph, or similar)

- Strong understanding of distributed systems, parallel processing, and large-scale data pipelines

- Solid SQL and data modeling fundamentals

- Experience with Docker and containerized deployments

- Experience with cloud platforms (GCP preferred, AWS/Azure acceptable)

- Strong backend/system design mindset (performance, scalability, reliability)

- Ability to work independently and take ownership

- Strong problem-solving skills in complex environments

- English level: B2+ 

- Availability to overlap with US business hours

Company offers:

- Long-term employment with possibilities for professional growth

- Fully remote work

- Reasonably flexible schedule

- 15 days of paid vacation

- Regular performance reviews

Тренувати, доводити до продакшну та інтегрувати моделі для
аналізу аудіо та текстової інформації в шумних, реальних
умовах.

ПРО ПРОЄКТ:
Ми будуємо ML-платформу для аналізу аудіо та текстової інформації — з
високою зашумленістю, складними акустичними умовами та великою
різноманітністю лексики. Це повний life-cycle: збір та підготовка даних,
тренування моделей (ASR, VAD, класифікація тексту, NER, ембеддинги),
експорт у продакшн (ONNX / TensorRT / Triton) та інтеграція у потокові
пайплайни (Apache Flink, RabbitMQ, Kafka). Кінцеві споживачі — аналітики,
які працюють з великими обсягами інформації; тому якість моделей та
якість їх інженерної реалізації одинаково критичні.

ЧИМ ВИ БУДЕТЕ ЗАЙМАТИСЯ
Тренувати та доводити до продакшну моделі у трьох суміжних доменах:

• ASR Speech-to-text — fine-tuning сучасних архітектур (CTC, RNN-T, TDT, attention-based) на шумних аудіо. PyTorch Lightning, NeMo, Hydra-конфіги, multi-GPU.
• VAD Voice activity detection — fine-tuning рекурентних та CNN-based моделей на спектрограмах, threshold optimization, ROC-аналіз.
• NLP / IR Текст та пошук — multi-label класифікація на трансформерах та класичних методах, NER, дедуплікація тексту (MinHash LSH) та аудіо (contrastive embeddings, SimCLR), векторний та повнотекстовий пошук.

— Експортувати моделі в ONNX, готувати TensorRT-плани (FP16, optimization profiles, dynamic shapes), інтегрувати в NVIDIA Triton (ensemble, BLS, dynamic batching, instance groups).
— Будувати продакшн-сервіси: FastAPI-фронти, асинхронні воркери на RabbitMQ / Kafka / S3 / Redis, інтеграція в Flink-пайплайни.
— Проводити ретельні бенчмарки: WER, F1 per-class, ROC-AUC, RTFx, throughput, A/B-тести з людьми розмітниками (Prodigy).

— Читати papers, відтворювати state-of-the-art підходи та адаптувати їх під наші дані.

— Версіонувати дані та моделі (DVC + MinIO/S3), трекати експерименти (Weights & Biases), писати тести (pytest), проходити code review.

ОБОВʼЯЗКОВІ ВИМОГИ

• 5+ років комерційного досвіду в ML / NLP / Information Retrieval. CV-досвід не потрібен.
• Python як основна мова — впевнене володіння сучасним Python (3.11+), типізація, async/await, написання чистого підтримуваного коду.
• PyTorch на рівні автора кастомних training loops — не лише Trainer.fit(), а й написання своїх loop-ів, distributed training (DDP, gradient accumulation, mixed precision), розуміння як працюють loss-функції під капотом (CTC, RNN-T, contrastive losses).
• Принаймні один глибокий досвід в одному з напрямків: ASR / sequence-to-sequence, класичний NLP на трансформерах та класичних методах, або Information Retrieval (BM25, dense retrieval, MinHash / LSH, ранжування).
• Здатність читати та відтворювати papers — брати модель або підхід з arXiv, розуміти trade-offs, адаптувати під свої дані, а не лише запускати готові скрипти.
• Інженерія продакшну — досвід доведення моделі від ноутбука до сервісу: експорт (ONNX / TorchScript), оптимізація інференсу, побудова REST / gRPC API, написання тестів (unit + integration).
• HuggingFace екосистема — впевнена робота з transformers, datasets, tokenizers, accelerate, evaluate, hub; досвід fine-tuning, custom training loops, кастомних токенайзерів (BPE, SentencePiece, WordPiece).
• Класичний ML — sklearn, XGBoost, threshold tuning для imbalanced multi-label задач, метрики Precision / Recall / F1 (macro/micro/per-class), ROC-AUC.
• Git, pre-commit, лінтери, CI — сприймати ці речі як норму, а не як перешкоду. Англійська — читання технічної документації та papers без труднощів.

БУДЕ ПЛЮСОМ

• NVIDIA Triton Inference Server — ensemble, BLS, Python backend, config.pbtxt.
• TensorRT — компіляція engine, optimization profiles, INT8/FP16 квантизація.
• ONNX Runtime — оптимізація графів, провайдери (CUDA / TensorRT / CPU).
• Data engineering — Apache Flink, Kafka, потокова обробка, DVC, data pipelines.
• Інфраструктура — Docker, Kubernetes, Helm, ArgoCD, GitLab CI, AWS (S3, CodeArtifact).

СТЕК, З ЯКИМ ВИ БУДЕТЕ ПРАЦЮВАТИ:
CORE Python 3.11+, uv, PyTorch, PyTorch Lightning, HuggingFace (transformers, datasets, tokenizers, accelerate), spaCy, sentence-transformers, sklearn, XGBoost.

ІНФЕРЕНС ONNX Runtime, TensorRT, NVIDIA Triton; FastAPI, Uvicorn, asyncio, Pydantic v2.

ДАНІ RabbitMQ, Kafka, Apache Flink; S3 / MinIO, Elasticsearch, PostgreSQL, Redis Stack.

MLOPS DVC, Weights & Biases, GitLab CI/CD, Kubernetes, ArgoCD; jiwer (WER), torchmetrics, scikit multilearn, Prodigy.

ЯК МИ ПРАЦЮЄМО:

• Маленька команда, низька бюрократія; рішення приймає інженер, який володіє контекстом.
• Кожна зміна моделі або інфраструктури має чіткі бенчмарки до/після — ми не «відчуваємо що краще», ми міряємо.
• Production-mindset з самого початку: будь-яка модель з ноутбука повинна мати план виходу на сервер.
• Документація, діаграми архітектур, чесні post-mortem-и, культура writing-it-down.

AI Product Engineer / AI-First Developer

We are looking for an AI-first engineer who can leverage modern AI tools to dramatically accelerate software development.

Our goal is not simply to integrate AI into products, but to rethink the development process itself.

You will work on rapid prototyping, MVP development, internal automation, AI-powered products, and client projects where development speed and efficiency are critical.

Responsibilities:

• Build software products using AI-assisted development workflows
• Use tools such as Claude Code, Cursor, OpenAI, Anthropic and modern AI ecosystems
• Rapidly prototype and validate product ideas
• Design and implement AI-powered features
• Build integrations with LLMs and AI services
• Optimize development processes through AI automation
• Collaborate with engineering and product teams

Requirements:

• Strong software engineering background
• Commercial experience with Python, JavaScript/TypeScript or similar technologies
• Experience using AI coding tools in production workflows
• Experience with OpenAI, Anthropic or other LLM APIs
• Understanding of prompt engineering and AI agent workflows
• Ability to quickly learn new technologies
• Strong problem-solving skills

Nice to have:

• Experience with RAG systems
• Experience with LangChain, LangGraph or LlamaIndex
• Experience building AI agents
• Startup or MVP development experience

Most importantly, we are looking for engineers who can demonstrate how AI helped them significantly increase development speed and productivity.

We’re looking for an AI Engineer to join our outsourcing team — not a pure ML researcher, but a pragmatic, data-driven backend engineer who knows how to put LLMs, vision APIs, and off-the-shelf models to work inside real products.

Most of our work isn’t training models from scratch — it’s understanding the business logic, collecting and cleaning data, wiring it into LLMs or services like AWS Textract, and shipping the result as a reliable API inside our existing platform.

If you’ve spent the last few years building APIs and integrations, you’re comfortable with data, and you’ve leaned hard into Cursor or Claude Code to deliver projects faster — this is for you.

What you’ll do

• Build and ship LLM-powered features: prompt design, data prep, passing context to the model, parsing and validating output, returning clean APIs.
• Design and implement integrations between our product and third-party AI services (OpenAI, Anthropic, Hugging Face models, AWS Textract, etc.).
• Take document-processing and computer-vision tasks end-to-end: ingest → Textract/vision API → post-process → structured output consumed by our backend.
• Write backend services and APIs in Node.js (our primary backend), dropping into Python when a task calls for it (model work, data scripts, fine-tuning).
• Fine-tune existing models and prompts — not from scratch, but iterating on what’s already in place to get better accuracy, cost, or latency.
• Do the unglamorous but critical work: data collection, cleaning, transformation, pattern-finding — often by letting an LLM do the heavy lifting on structured and unstructured input.
• Maintain and improve existing AI and automation workflows already running in production.
• Monitor cost and performance of model/API usage, propose optimizations, and forecast costs for new features.
• Prepare and present demos and solution overviews to U.S.-based clients.
• Document architecture, prompts, and pipelines in Confluence.

What we’re looking for

• 2+ years shipping production backend systems, with meaningful hands-on experience integrating LLMs or AI APIs into real products.
• Strong in Node.js with the flexibility to work in Python — or a Python engineer who’s comfortable committing Node.js code. We need someone fluent on both sides; pure-Python candidates won’t be a fit.
• Solid grasp of algorithms and data structures — enough to write custom logic when an LLM or library can’t cover the case.
• Real experience with LLM integrations: OpenAI, Anthropic, or similar. Prompt engineering, function/tool calling, structured output, retrieval, evaluation.
• Familiarity with the Hugging Face ecosystem — picking models, running inference, fine-tuning where it makes sense.
• API and integrations background: REST, auth, webhooks, rate limits, retries, idempotency — the stuff that makes integrations not break at 2 a.m.
• Comfortable with data work: collecting, cleaning, transforming, and analyzing data (SQL, pandas, or the Node equivalents).
• Working knowledge of AWS — especially Textract, Lambda, S3, and the services around document and data pipelines. Bonus for Athena, Glue, Kinesis, SageMaker.
• Exposure to NLP and Computer Vision concepts — enough to pick the right tool and evaluate results, not necessarily to train SOTA models.
• Familiarity with CI/CD and deploying AI-powered services to production.
• Experience building chatbot workflows — conversational flows, multi-turn logic, context management — is a plus, as this is among our planned projects.
• AI-native delivery workflow. You use Cursor or Claude Code daily and know how to ship a project with minimal hand-written code — scoping work for the agent, reviewing generated code critically, orchestrating multi-step tasks, and getting to shipped quality faster than a traditional workflow. If you can’t describe how you use these tools to deliver, this role isn’t the right fit.

Nice to have

• Experience fine-tuning open-source LLMs or vision models on domain-specific data.
• Background in fintech, healthcare, or construction domains.
• Experience with vector databases, RAG pipelines, or agentic workflows.

What we offer

• Competitive salary with regular reviews.
• Support for individual entrepreneurs with accounting assistance.
• Fully remote work.
• A clear path for professional development and growth.
• A friendly team environment and engaging team-building activities (online and offline).

PwC is a global network of more than 370,000 professionals in 149 countries that turns challenges into opportunities. We create innovative solutions in audit, consulting, tax and technology, combining knowledge from all over the world.

PwC SDC Lviv, opened in 2018, is part of this global space. It is a place where technology is combined with team spirit, and ambitious ideas find their embodiment in real projects for Central and Eastern Europe.

What do we guarantee?

• Work format: Remote or in a comfortable office in Lviv - you choose.
• Development: Personal development plan, mentoring, English and Polish language courses.
• Stability: Official employment from day one, annual review of salary and career prospects.
• Corporate culture: Events that unite the team and a space where everyone can be themselves.

Join our dynamic AI team and be at the forefront of innovation, working on transformative projects for some of the most recognized companies worldwide. As an AI Consultant, you will participate in the implementation and development of AI-powered solutions across a broad range of applications, from Gen AI tools to data analytics fraud detection systems.

Key Responsibilities:

• Participate in AI projects from inception to completion, ensuring timely delivery of high-quality solutions;
• Solution Development: Design and implement cutting-edge AI and GenAI solutions, including Retrieval-Augmented Generation (RAG) for knowledge retrieval, prompt optimization, and fine-tuning of large language models (LLMs);
• Apply AI techniques to areas such as fraud detection, satellite imagery analysis, time-series forecasting, and automated data quality validation to enhance decision-making and automation;
• Develop web applications (FE / BE / cloud architecture) enabling users to interact with AI systems;
• Client Interaction: Work closely with clients to understand their unique needs and provide expert guidance and support throughout the project lifecycle.

Requirements and skills:

• 2+ years of professional experience in this or similar area;
• Experience working on AI/ML projects, in areas such as Generative AI, NLP, Computer Vision or Machine Learning model development and deployment;
• University degree in Mathematics or a similar field is an advantage;
• Programming skills in Python (pandas, plotly, numpy);
• Experience with Full stack development (JavaScript) is a significant plus.
• Experience with SQL databases; familiarity with NoSQL is a plus;
• Experience with generative AI models is a plus;
• Fluent in English (level B2 or higher).

Policy statements:
https://www.pwc.com/ua/uk/about/privacy.html

We are looking for an Autonomous systems engineer with a background in computer vision, control theory and mathematical modelling. The ideal candidate will have a strong math background, experience with autonomous systems, modelling and control design. 

Required Qualifications: 

• 2 years of hands-on experience with classical computer vision
• Understanding of geometrical computer vision principles 
• System identification and control
• Sensor fusion/signal processing
• Proficiency in C++ and/or experience with Python
• Experience with Linux and single-board computers
• Experience with PID controllers tuning in embedded or autonomous systems
• Ability to quickly navigate through recent research and trends in computer vision and autonomous systems
• Relevant work experience or education in STEM field

Nice to Have:

• Experience with SLAM and/or Visual-Inertial Odometry (VIO)
• Matlab
• Experience with PX4, betaflight, Ardupilot 
• Familiarity with neural networks and common CV frameworks/libraries (OpenCV, NumPy, PyTorch, ONNX, Eigen, etc.)
• Experience with simulation tools (Gazebo, AirSim)
• SITL, HITL testing
• ROS2

We’re focusing on:

• Complex document processing pipelines
• Knowledge retrieval systems powered by LLMs and RAG
• Building production-ready GenAI solutions with real business value

I’m open to candidates of different experience levels — what matters most is strong problem-solving skills, curiosity, and hands-on experience.

You should have:

• Solid understanding of machine learning and NLP algorithms
• Practical knowledge of how LLMs and Retrieval-Augmented Generation (RAG) work

• Previous experience with real-life AI/ML projects (commercial) - at least 1 year

   

At Avanquest, we build software that makes digital life genuinely easier, for everyday users and professionals alike, all over the world. Smooth document management, faster and safer devices, and browsing without the hassle: we spot the everyday frustrations and fix them. Millions of people around the world count on us. And we're just getting started.

We're growing fast, and we're hungry for more. With teams across North America and Europe, we tap into a wide range of perspectives to push our thinking further. AI isn't a buzzword here, it's a real engine for change. We use it to sharpen our products, break new ground, and build experiences that actually move the needle.

Creativity and boldness are welcome at every level. We don't want order-takers, we want builders. The best idea wins, no matter who it comes from. Here, personal ambition and team spirit don't compete, they feed each other. If you want to stretch yourself, make a real impact, and win as a team, you're in the right place.

What you'll be responsible for:

Model Serving & API 

• Evaluate and deploy open-source LLMs via vLLM, Ollama, or TGI on GPU infrastructure; 
• Design and maintain a REST API with auth, rate limiting, versioning, and API documentation; 
• Optimize inference: quantization, batching, and concurrency tuning for latency/cost trade-offs. 

Web App Integration 

• Integrate AI features into our web apps and document processing platforms; 
• Build AI-powered UI components: chat interfaces, inline suggestions, smart search, and summarization widgets; 
• Collaborate with frontend engineers on UX patterns specific to async and streaming AI responses. 

Document Orchestration 

• Design multi-step orchestration pipelines for document ingestion, parsing, classification, and extraction; 
• Integrate OCR, layout detection, and chunking strategies for PDFs, Word docs, spreadsheets, and scanned images; 
• Build RAG pipelines with hybrid retrieval (dense + sparse) over document corpora; 
• Implement task queues and async workers to handle high-volume document processing reliably. 

Platform & Collaboration

• Write technical docs, so the platform is maintainable by the whole team and accessible for technology partners; 
• Stay current on the open-source model ecosystem and advise on model selection and upgrades.

The profile we're looking for:

• 3+ years of experience across backend, API design, and web technologies;
• Proven track record deploying or integrating LLMs in production (open-source models strongly preferred);
• Hands-on knowledge of REST API design and at least one API framework;
• Experience building AI features in web apps, including streaming and async response handling;
• Familiarity with document processing workflows — OCR, parsing, classification at scale;
• Comfortable designing multi-step orchestration pipelines with task queues, retries, and failure handling;
• Strong communication skills; able to reason about trade-offs across latency, cost, and accuracy with stakeholders.

Here's what we offer:

Working at Avanquest means thriving in an environment where performance and well-being go hand in hand. We believe in flexibility, balance, and ongoing professional growth.

Here's what's waiting for you:

• A flexible hybrid work model, with the option to work remotely from abroad.
• Competitive pay that recognizes your value and your talent.
• A full insurance package for you and your family.
• A bonus program that rewards your performance and your drive.
• A generous vacation and time-off policy, because we believe in real rest.
• We're committed to growing your potential and investing in your professional development.
• A stimulating, diverse, and multicultural environment where every perspective counts.

We value and support diversity. We are committed to providing an environment that promotes inclusion and respect for all. We therefore encourage women, people of all gender identities, Aboriginal people, and people with disabilities to apply for our positions.

Visit our website: www.avanquestgroup.com

CodeTiburon is looking for a Senior Backend Engineer (LLM & AI Infrastructure) to join our team and work closely with one of our long-term clients.

About the project:

We are a deep-tech company building state-of-the-art LLM-based assistants augmented with knowledge graphs. The platform focuses on combining large language models with structured knowledge systems to create more accurate, reliable, and scalable AI assistants.
 

The project involves building robust backend infrastructure that powers AI applications, enabling scalable model inference, retrieval systems, and knowledge graph integrations within a multi-tenant SaaS environment.
 

Responsibilities:
 

• Architect, deploy, and operate scalable backend services and multi-tenant SaaS systems in Kubernetes-based cloud environments
• Design and operate high-throughput data pipelines (batch and streaming)
• Build APIs and services integrating LLM inference, retrieval systems, and knowledge graphs
• Productionize research-grade AI systems into reliable distributed systems
   

Requirements (Must Have):
 

• 7+ years of backend engineering experience
• Strong experience with data pipelines and SaaS architectures
• Strong proficiency in Python
• Deep understanding of distributed systems and cloud-native environments
• Strong hands-on experience with Kubernetes in production environments. Candidates should be comfortable deploying, operating, scaling, and troubleshooting distributed applications on Kubernetes and have practical experience with its core ecosystem (networking, storage, observability, autoscaling, and CI/CD integration).
   

Nice to Have:
 

• Go and/or Scala experience
• Hands-on experience with LLM systems (RAG, model serving, evaluation)
• Experience with knowledge graphs, vector databases, or hybrid retrieval architectures
  
   

Ideal for engineers who enjoy building production-grade systems around cutting-edge AI research.

 

If this sounds like you and your experience aligns with most of the qualifications above, we’d love to hear from you. Please send us your CV.

Thank you for your interest. Each application is carefully reviewed, and candidates whose experience and background best align with the role will be contacted regarding the next steps.

Full Remote | Full-Time | b2b | Flexible Schedule|Product Company

Overview

At eMenu, we are revolutionizing the hospitality industry through innovative iPad menus served to guests in restaurants instead of traditional paper menus.

Our mission is to transform how people interact with menus and dining experiences, setting new standards for customer engagement and operational excellence.

As we continue to grow, we are building intelligent, responsive systems – including a conversational AI Waiter and upgrading our internal tools. You will contribute to redefining the smart restaurant experience by building robust backend systems, integrating language models, and developing automated features that empower both our users and internal teams.

Role Summary

We are looking for a hands-on PythonAI Engineer to take ownership of internal automation systems, tackle complex backend integration challenges, and contribute to the backend systems supporting our conversational “AI Waiter.”

This role emphasizes strong software engineering fundamentals, project ownership, and problem-solving. While your primary focus will be backend development, you will heavily utilize AI-driven tools, automation systems, and third-party integrations to get the job done.

Key Responsibilities

• AI Waiter Contributions: Contribute to the backend systems and integrations that power our conversational AI Waiter.
• AI Tools & Data Processing: Develop and improve internal tools by integrating LLMs for data processing, alongside other third-party AI services (e.g., text and image processing APIs).
• Backend Engineering & Automations: Build and maintain internal APIs using Python, FastAPI, and SQL databases. Develop backend automations, alerting systems, and complex third-party API integrations.
• Testing & Code Quality: Write maintainable, robust code and implement automated tests to ensure system reliability.
• Web Architecture: Design clear, scalable APIs to ensure seamless and reliable client-server data flow.
• Cloud Infrastructure: Work within an AWS cloud environment and support application deployments when needed.

Requirements

Must-Have:

• 3–5 years of experience in software development with a strong focus on backend engineering.
• AI Integration: Practical, hands-on experience integrating and working with Large Language Models (LLMs) via APIs.
• Strong proficiency in Python and modern frameworks (e.g., FastAPI).
• Solid experience working with SQL databases.
• Deep understanding of web architecture, REST APIs, and client-server interaction.
• Cloud Experience: Familiarity with AWS or similar cloud platforms to understand the environment and support deployments.
• Fluency in English (Upper-Intermediate or higher) and one additional language (Ukrainian, Russian, or Hebrew).

Working Style & Expectations:

• Project Ownership: Ability to work independently with minimal supervision, define solutions end-to-end, and take responsibility for systems in production.
• Bias for Action: Strong prioritization skills with a focus on delivering production-ready solutions quickly.

Nice to Have:

• Reverse Engineering: Ability to analyze and work with undocumented APIs or systems.
• Familiarity with recommendation systems or predictive modeling.
• Experience with frontend frameworks (e.g., Vue.js).

Work Environment and Schedule

• Salary: Up to $4,500 per month.
• Contract: B2B contract – unlimited.
• Time Off: 10 calendar days of PTO per year; up to 5 sick days per year.
• Stability: Long-term role with a focus on retention.
• Flexible Schedule: 40 hours per week, fully flexible distribution (aligned mostly with European hours, occasional US overlap).
• Minimal Meetings: No daily standups, weekly updates only.

Interview Process

1. Step 1 – Introductory Call
2. Step 1.5 – Take-Home Test (before the technical interview)
    
3. Step 2 – Technical Interview with Ilya (~1 hour total)
4. Step 3 – Cultural Fit Interview

CodeTiburon is looking for an AI Research Engineer — Neuro-Symbolic Reasoning & Generative AI to join our team and work closely with one of our long-term clients.
 

About the Project

Our client is an applied AI lab specializing in formal knowledge representation and next-generation reasoning. The project is dedicated to building “semantic AI” capable of deep, grounded reasoning over complex structures such as texts, arguments, and intellectual traditions.
 

The core mission is to combine the power of modern LLMs with the rigor of neuro-symbolic methods and Knowledge Graphs. By focusing on domains with the highest logical standards, the team aims to set new benchmarks for responsible and intelligent AI behavior across the industry.
 

About the Role:

You will be employed by CodeTiburon and embedded into the client’s research team on a long-term basis. Working alongside a Senior Applied Scientist, you will help transform research ideas into production-quality systems and reproducible experiments.

While the Applied Scientist defines research directions and designs novel algorithms, you will be responsible for implementing experiments, fine-tuning models, building evaluation frameworks, developing data and reasoning pipelines, and iterating toward robust, production-ready solutions.

You will serve as a key engineering partner in the research process—proposing implementation strategies, identifying engineering constraints early, and translating hypotheses into measurable results.

 

Topics You Will Work On:

• Experiment Implementation. Translate research designs from the Applied Scientist into clean, reproducible Python experiments—covering neuro-symbolic architectures (LTN, DeepProbLog, LARK), hybrid LLM+KG pipelines, and RAG systems.
• Knowledge Graph & Ontology Engineering. Build and maintain tooling around RDF/OWL 2 ontologies, SPARQL/Cypher queries, and graph databases (Neo4j, Amazon Neptune) to feed downstream reasoning modules.
• RAG/KG Pipeline Development/Integration. Implement and iterate on retrieval-augmented generation/KG pipelines—combining dense, sparse, and structured retrieval over heterogeneous corpora with provenance tracking.
• LLM Fine-Tuning & Evaluation. Run supervised and RLHF/DPO fine-tuning experiments; build evaluation harnesses that include symbolic verification layers, benchmarks, and regression suites.
• Research Infrastructure. Own the experiment tracking, dataset pipelines, and MLOps scaffolding (MLflow, SageMaker, Vertex AI) that let the team iterate quickly and reproduce results reliably.
• Literature & Prototyping. Stay current with relevant publications; rapidly prototype ideas from newly published methods and assess their fit against the client’s goals.
  
   

Required Qualifications
 

Education:

Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, AI Planning, Machine Learning, Cognitive Science, Formal methods, or a closely related field.
 

Language Skills:

Professional working proficiency in English, both written and spoken, with the ability to participate in technical discussions, read and implement research papers, document findings, and collaborate effectively in an international research environment (Strong B2/C1).

Core Technical Skills:

• Generative AI / LLMs: solid working knowledge: transformer architecture, prompt engineering, RAG, tool use, fine-tuning (SFT/LoRA);
• Machine Learning: proficient: supervised/unsupervised learning, representation learning, experiment design;
• Neuro-Symbolic Concepts: familiar: exposure to at least one framework (s.t. LTN, DeepProbLog, NSCL, LARK) or symbolic AI coursework; eager to deepen;
• Knowledge Graphs: working knowledge: graph data models, SPARQL or Cypher queries, at least one graph DB (Neo4j or equivalent);
• Software Engineering: strong production Python; unit testing, version control, CI basics
   

Experience:

• Proven ability to independently implement research ideas, build reproducible experiments, and contribute to production-ready AI systems.
• Demonstrated ability to implement models and algorithms from research papers with minimal hand-holding.
• 3–5 years of hands-on experience in ML/AI engineering, research engineering, or a closely related role (internships and research assistant positions count).
• Experience with experiment tracking tools (MLflow, Weights & Biases, or similar) and reproducible research practices.
• Experience working with cloud-native ML infrastructure on AWS, GCP, or Azure.
   

Preferred Qualifications:

• Exposure to formal knowledge representation: OWL 2, RDF/RDFS, description logics, or first-order logic formalisms.
• Familiarity with agentic AI frameworks (tool-use chains, multi-step planning, multi-agent coordination).
• Experience with LLM evaluation and red-teaming for factual accuracy, logical consistency, or safety.
• Contributions to open-source ML/NLP/KR projects or co-authorship on an arXiv pre-print or workshop paper.
• Exposure to formal verification, SAT/SMT solvers, or answer set programming.
• Experience with low-resource or domain-specific fine-tuning of foundation models.
• Familiarity with graph neural networks or heterogeneous graph transformers.
• Experience with AI coding tools such as Claude Code or Cursor.
• Proven ability to deliver production-ready artifacts.
   

Responsibilities:

• Implement, run, and iterate on experiments designed by the Applied Scientist; maintain clean, well-documented, reproducible code.
• Build and maintain RAG pipelines, knowledge graph integrations, and neuro-symbolic prototype systems.
• Design and execute evaluation harnesses—combining automated metrics, symbolic checks, and human evaluation—to measure model quality and catch regressions.
• Keep experiment infrastructure (data pipelines, tracking, compute provisioning) reliable and easy for the whole team to use.
• Read relevant papers and proactively surface implementation options or potential issues before they become blockers.
• Collaborate daily with the Applied Scientist, ML engineers, and content teams to align research outputs with product requirements.
• Contribute to internal documentation, design reviews, and code reviews; grow your skills through mentorship from senior researchers.
• Uphold scientific rigour, reproducibility, and responsible AI practices in every piece of work you ship.
• Working closely with the production owners.

If this sounds like you and your experience aligns with most of the qualifications above, we’d love to hear from you. Please send us your CV.

Thank you for your interest. Each application is carefully reviewed, and candidates whose experience and background best align with the role will be contacted regarding the next steps.

Quantum is a global technology partner delivering high-end software products that address real-world problems. 

We advance emerging technologies for outside-the-box solutions. We focus on Machine Learning, Computer Vision, Deep Learning, GIS, MLOps, Blockchain, and more.

Here at Quantum, we are dedicated to creating state-of-the-art solutions that effectively address the pressing issues faced by businesses and the world. To date, our team of exceptional people has already helped many organisations globally attain technological leadership.

We constantly discover new ways to solve never-ending business challenges by adopting new technologies, even when there isn't yet a best practice. If you share our passion for problem-solving and making an impact, join us and enjoy getting to know our wealth of experience!

About the position

Quantum is expanding the team and has brilliant opportunities for a Senior DS / AI Engineer. The client is a technological research company that utilises proprietary AI-based analysis and language models to provide comprehensive insights into global stocks in all languages. Our mission is to bridge the knowledge gap in the investment world and empower investors of all types to become "super-investors." Through our generative AI technology implemented into brokerage platforms and other financial institutions' infrastructures, we offer instant fundamental analyses of global stocks alongside bespoke investment strategies, enabling informed investment decisions for millions of investors worldwide.

Must have skills:

• 5+ years of commercial experience as a Data Science / AI Engineer
• Strong Python skills and software engineering fundamentals
• Strong understanding and experience in the development of high-load production systems
• 2+ years of experience with LLM and NLP-related tasks
• Hands-on experience with RAG and vector DBs
• Knowledge of modern DL architectures
• Experience with at least one of the Deep Learning frameworks (Tensorflow, PyTorch)
• Experience with SQL and NoSQL databases
• Good knowledge of Kubernetes
• Strong experience in development with AI tools (Claude Code, Cursor)
• At least an Upper-Intermediate level of English (spoken and written)

Nice to have skills:

• Familiarity with MCP (Model Context Protocol)
• Experience with production LLM frameworks (vLLM)
• Experience in training LLMs
• Experience with Cloud Computing Platforms (AWS, GCloud, Azure)
• Participation in Kaggle competitions

Your tasks will include:

• Full-cycle data science projects
• Data analysis and data preparation
• Development of NLP solution and AI-based chatbots
• Developing models and deploying them to production
• Sometimes, this will require the ability to implement methods from scientific papers and apply them to new domains

We offer:

• Delivering high-end software projects that address real-world problems
• Surrounding experts who are ready to move forward professionally
• Professional growth plan and team leader support
• Taking ownership of R&D and socially significant projects
• Participation in worldwide tech conferences and competitions
• Taking part in regular educational activities
• Being a part of a multicultural company with a fun and lighthearted atmosphere
• Working from anywhere with flexible working hours
• Paid vacation and sick leave days

Join Quantum and take a step toward your data-driven future.

About the Project

The client is looking for a Software Engineer who operates at the intersection of high-scale frontend engineering and cutting-edge Applied AI.

In this role, you won’t just "build UI", you will design and deliver intelligent, cloud-native user experiences for our Maritime Intelligence Agentic platform. Our systems are used by defense agencies, governments, and global enterprises to secure trade and enforce compliance at sea. You will be expected to work autonomously, influence frontend architecture and UX standards, and significantly raise the bar for AI-assisted development within the team.

Required skills:

• A Professional Engineer: You have 7+ years of professional frontend or full-stack engineering experience, including 2+ years of experience building AI-powered products, agentic interfaces, or intelligent workflows in production at scale.
• An AI-Native Engineer: You are excited about agentic development and AI-enhanced user experiences. You are proficient in AI-based development workflows utilizing tools like Claude Code, Cursor, or Copilot in a highly autonomous fashion, and are a strong, independent individual contributor who can work effectively alone or in small, ad-hoc groups.
• Frontend & Cloud Architecture: You have proven experience building modern frontend applications with React, Next.js, TypeScript, GraphQL/REST APIs, and distributed cloud-based architectures. Experience with real-time systems, event-driven architectures, and cloud-native environments is highly valued.

• A Craftsman: You take pride in clean code, thoughtful UX/UI design, frontend performance, accessibility, and production-grade quality. You are accountable, independent, and thrive in ambiguous environments.

   

Technical Requirements

• Frontend Stack (Mandatory): Proven expertise with React.js, Next.js, TypeScript, modern frontend architecture patterns, state management, and component-driven development.
• AI & Agentic Interfaces: Experience integrating AI capabilities into frontend applications, such as conversational UI, AI copilots, streaming responses, or agentic workflows. Experience with frameworks such as LangChain, LangGraph, OpenAI SDKs, Vercel AI SDK, or similar is a strong plus.
• Cloud & Infrastructure: Solid understanding of modern frontend deployment environments, CI/CD pipelines, cloud-native applications, and observability practices. Familiarity with AWS, Kubernetes, Terraform, or serverless environments is a plus.

• Nice to Have: Experience with backend technologies such as Python, Node.js, GraphQL services, or distributed systems.

   

Scope of work:

• Architect & Build: Design and deliver scalable, responsive, and high-performance frontend applications, primarily using React/Next.js, within a distributed system architecture.
• AI Integration: Lead the integration of Generative AI capabilities into frontend experiences, including AI-powered workflows, copilots, conversational interfaces, and real-time intelligence visualization tools.
• Frontend Operations & Observability: Implement monitoring, analytics, performance optimization, and observability practices to ensure reliability, usability, and smooth user experience in production.
• Elevate Engineering: Drive frontend engineering quality and speed by implementing AI-SDLC practices, enforcing high standards through code reviews, component testing, E2E automation, and continuous UX/performance evaluation.
• Mentor & Innovate: Evaluate emerging AI and frontend tooling, mentor fellow engineers, and contribute directly to the evolution of our frontend architecture and technical roadmap.

AI & Innovation Specialist

Location: Kolding, Denmark – On-site
Company: Bixter
Industry: International Recruitment, Education & Workforce Innovation

About Bixter

Bixter is an international recruitment and education platform connecting global talent with European employers in sectors such as agriculture, logistics, food processing, hospitality, and healthcare. 

We are now looking for an AI & Innovation Specialist to help us accelerate automation, digital transformation, and AI-driven growth across recruitment, education, operations, and customer experience.

Your Mission

You will lead the development and implementation of AI-powered systems and innovative workflows that improve efficiency, scalability, and user experience across the Bixter ecosystem.

This role combines AI implementation, automation, product innovation, data-driven optimization, digital transformation, and emerging technology research.

You will work directly with leadership and have a major influence on how Bixter evolves over the coming years.

Key Responsibilities

AI & Automation

• Implement AI tools across recruitment, education, operations, and customer support 
• Develop automated workflows using AI platforms and integrations 
• Optimize processes with smart, up-to-date AI solutions 
• Build AI-assisted communication systems and internal tools 
• Identify opportunities for improvement and make a measurable difference 

Innovation & Product Development

• Research emerging AI technologies and identify practical business applications 
• Support the development of internal digital projects 
• Contribute to new AI-driven services and products 
• Analyze market trends and recommend innovation strategies 

Data & Analytics

• Use data insights to improve business performance 
• Build dashboards, reporting systems, and operational analytics 
• Identify process bottlenecks and opportunities for optimization 

Cross-Functional Collaboration

• Work with recruitment, marketing, education, and operations teams 
• Train colleagues in AI tools and best practices 
• Help create an innovation-driven culture within the company 

Requirements

Must-Have

• Experience with AI tools, automation platforms, or digital transformation projects 
• Strong understanding of ChatGPT, generative AI, and modern AI workflows 
• Experience with workflow automation tools such as Zapier, Make, n8n, or similar 
• Analytical mindset and strong problem-solving skills 
• Excellent communication skills in English 
• Ability to work independently and take initiative 

Nice-to-Have

• Experience with CRM systems 
• Experience with LMS or online education platforms 
• Knowledge of prompt engineering 
• Basic coding skills, such as Python, JavaScript, or APIs 
• Experience with data analytics or BI tools 
• Experience in recruitment, HR-tech, EdTech, or SaaS 

What We Offer

• Opportunity to shape the future of an international growth company 
• Direct impact on strategic innovation and AI adoption 
• Flexible working environment 
• High level of responsibility and autonomy 
• International team and projects 
• Possibility to grow into a leadership role in AI & innovation 

Ideal Candidate

You are curious, proactive, and passionate about using AI to solve real business problems. You enjoy testing new technologies, improving systems, and creating scalable solutions that make organizations smarter and more efficient.