Jobs ML / AI

Опис:

Ми — AI-компанія, яка стрімко зростає. Ми виграли грант Європейського Союзу €500K на 24 місяці на R&D-надбудову до продукту — і шукаємо ML-лідера, який її збудує.

MedicallAI — це AI-платформа, що бере на себе всю комунікацію клініки з пацієнтами: дзвінки, повідомлення, прогнозування неявок і виявлення критичних станів. 

Що вже є:

• Працюючий комерційний продукт — AI-комунікаційна платформа для кол-центру клінік, із підтвердженим кейсом у Польщі (Doctorpro.pl).
• Реальні дані: записи дзвінків від партнерської клініки + DPA на R&D.
• Грант €500K на 24 місяці.
• Ринок: ЄС (Німеччина, Австрія, Польща, Румунія) + Україна.

Що належить зробити:

• SER (Speech Emotion Recognition): fine-tuning WavLM / HuBERT, 5 класів емоцій, ціль F1 ≥ 0.75, Recall для fear/anxiety ≥ 0.88.
• Emergency Classifier: мультимодальний (аудіо + текст, Cross-Modal Fusion), 12 критичних станів, Recall ≥ 0.92, time-to-detection ≤ 8 сек.
• PCIE (прогноз неявок): цільове зниження no-show на 10–15%.
• Edge-deployment під GDPR: стиснення моделей для on-premise розгортання у клініках ЄС.
• Data pipeline: збір через SIP, анонімізація (PII masking, k-anonymity, differential privacy), GDPR-compliant сховище.

Горизонт — 24 місяці гранту: довести три ML-модулі від TRL 4 до TRL 7, вивести продукт на 20–30 клінік і підготувати компанію до Seed-раунду €2–3M.

Must-have:

• 5+ років ML / AI engineering.
• Глибоке знання Speech / NLP / emotion recognition.
• Hands-on: пишеш код, а не тільки керуєш.
• Досвід production deployment ML-моделей.
• Досвід роботи в ML-команді 2–3 людини та готовність очолити збір своєї команди.
• Англійська Upper-Intermediate (B2)+.

Буде плюсом:

• Науковий ступінь (PhD / кандидат) у ML / Speech / NLP.
• Досвід у healthcare / medical AI.
• Робота з чутливими даними та приватністю (GDPR / HIPAA-подібні вимоги).
• Публікації чи конференції (NeurIPS, ICML, Interspeech).
• Досвід збору команди з нуля.
• Edge-deployment: NVIDIA Jetson, ONNX, TensorRT.

Що пропонуємо:

• Ти — перший ML-найм: формуєш стек і команду під 24-місячний грантовий проект із виходом на Seed.
• Прямий вплив на продукт і архітектуру, автономія в межах цілей.
• Команда A-гравців поруч; рік у нас = 5 років у корпорації за швидкістю росту.
• Винагорода обговорюється індивідуально: фікс + бонус від milestones гранту.

Поля форми Djinni:

• Зарплата: обговорюється індивідуально (фікс + бонус від milestones гранту)
• English: Upper-Intermediate / B2+
• Досвід: 5+ років
• Категорія / домен: Machine Learning / AI · Healthcare / MedTech
• Формат: Україна / remote / гібрид

A-GOS is a VC-backed AI startup building an intelligent procurement and catering platform for the maritime industry.

We are now looking for an AI Engineer with practical experience in knowledge graphs, ontologies, and AI agents.
 

The Challenge

One of our main tasks is generating optimal weekly menus for vessel crews.

The system must consider:

• Ingredients available on board
• Quantities, prices, and expiration dates
• Crew nationalities and dietary, religious and cultural restrictions
• Consumption and nutritional norms
• Budget and food waste
• Recipe compatibility and menu diversity

Today, much of this logic is handled through Google OR-Tools. However, even with more than 500 recipes in our database, strict recipe structures often make it impossible to generate an optimal menu.

We want to make the system more intelligent.

It should be able to create valid recipe variations by replacing ingredients only when the substitution truly makes sense. The system should understand the ingredient’s role, taste, texture, cooking method, cuisine, nutrition, restrictions, and compatibility with other ingredients.
 

What You Will Work On

• Building a knowledge graph for ingredients, recipes, cuisines, restrictions, and substitution rules
• Designing the domain ontology and semantic model
• Developing intelligent ingredient substitution logic
• Building AI agents that reason over recipes, inventory, and crew requirements
• Integrating the knowledge layer with Google OR-Tools and our existing platform
• Creating explainable logic for generated recipes and menu decisions

What We Expect

• Practical experience with knowledge graphs or ontology design
• Experience developing AI agents or LLM-based systems
• Strong Python skills
• Understanding of semantic modelling, structured reasoning, and retrieval
• Ability to transform complex business rules into a scalable architecture
• Strong ownership and product thinking

What matters is that you have built a real system using knowledge graphs or ontologies and can explain your personal contribution.

Experience with Neo4j, RDF, OWL, SPARQL, GraphRAG, LangGraph, LangChain, LlamaIndex, or similar technologies would be a plus.

Why A-GOS

• Early-stage VC-backed startup
• Real and technically challenging AI product
• Direct influence on product and architecture
• Remote work and flexible schedule
• Small team with minimal bureaucracy
• Potential equity based on long-term contribution

How to Apply

Please briefly describe a real project where you worked with knowledge graphs, ontologies, RAG, semantic models, or AI agents.

Tell us what problem you solved, which technologies you used, what you personally built, and how it was integrated into the final system.

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 PwC's Advanced Technology Solutions team as an AI Engineer, where you will contribute to AI and data science solutions for leading global clients. This role is suitable for developers and engineers who want to build, deploy, and scale machine learning systems and AI-powered applications in a dynamic consulting environment.

We are looking for candidates who are strong in Python, confident working with data, and capable of turning complex business challenges into reliable, production-ready AI solutions while collaborating with clients across Western Europe and the USA.

Key Responsibilities:

• Design, develop, and deploy AI and Machine Learning solutions. 
• Build Python-based applications leveraging Generative AI, LLMs, RAG, NLP, Computer Vision, and Data Science techniques. 
• Participate in the full project lifecycle, from requirements gathering through deployment and ongoing support. 
• Collaborate with clients and internal teams to understand business challenges and translate them into scalable technical solutions. 
• Work with structured and unstructured data to develop AI-driven applications. 
• Actively leverage AI-powered development tools such as GitHub Copilot, Cursor, Claude Code, and ChatPwC to enhance productivity, improve code quality, accelerate delivery, and solve complex problems responsibly. 

What You Bring:

• 1–2+ years of experience in AI, Machine Learning or Software Engineering. 
• Strong Python programming skills (e.g. pandas, numpy, scikit-learn). 
• Hands-on experience with Generative AI, LLMs, RAG, NLP, Machine Learning, or Computer Vision. 
• Experience working with SQL databases. 
• Understanding of the ML lifecycle, including model training, evaluation, deployment, and monitoring. 
• Strong analytical and problem-solving skills. 
• English B2+. 

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

We are looking for a Prompt Spec Engineer who will define how our AI systems communicate, reason, and deliver high-quality outputs across products powered by LLMs.
 

You will be responsible for designing prompt/spec architectures, building evaluation systems, and ensuring that AI responses are consistent, reliable, and production-ready across RAG systems, AI agents, and automation workflows.

What you will do:
 

• Design and evolve prompt/spec architecture for AI products, LLM services, RAG systems, and AI agents, defining prompt structures, model behavior rules, response formats, and quality criteria.
• Develop, optimize, and adapt prompts for different LLMs and use cases, considering output quality, context limitations, cost, and system stability.
• Build and maintain AI evaluation processes including test scenarios, golden datasets, regression testing, and A/B experiments for LLM performance measurement.
• Analyze AI outputs, identify root causes of issues (hallucinations, missing context, retrieval problems, incorrect or unsafe responses), and define improvements.
• Collaborate with AI Engineers and Product Managers to implement prompt solutions into production systems, RAG pipelines, AI agents, and automation workflows, translating business needs into technical specifications.
• Work with LLM evaluation and monitoring tools (such as PromptFoo, Langfuse, and similar solutions) to track metrics, prompt versions, response quality, and system performance.
• Create and maintain structured documentation: prompt specs, evaluation frameworks, usage guidelines, limitations, and best practices for safe and reliable AI behavior.

What we expect from you:
 

• 2+ years of experience in LLM-related roles such as Prompt Engineering, AI Product Operations, AI Evaluation, or similar.
• Hands-on experience designing and optimizing prompts for different LLMs with a strong understanding of model behavior, strengths, and limitations.
• Experience building prompt/spec systems including prompt structure design, behavior rules, response formatting, testing, and versioning.
• Strong experience in AI evaluation: test case design, output analysis, issue detection, and iterative improvement of model performance.
• Understanding of RAG systems, AI agents, structured outputs, tool calling, and principles of reliable LLM system design.
• Ability to collaborate with engineering and product teams, translate business requirements into AI specifications, and document solutions clearly and consistently.
• Upper-Intermediate (B2+) English 
   

What we offer

• Competitive compensation depending on experience
• Work on production-level AI systems (LLMs, RAG, AI agents, automation workflows)
• Office-based work in Lviv with the possibility of a hybrid schedule.
• Direct impact on AI product quality and system behavior
• Access to modern LLM tools and evaluation frameworks
• Professional growth in a fast-moving AI-focused environment
• Opportunity to shape prompt engineering standards inside the company
• Relocation support for candidates from other cities, including assistance with moving and adaptation in Lviv.

🟠 Details: we are looking for a Senior Computer Vision & Machine Learning Engineer to join our team and work on innovative AI and Computer Vision solutions for international clients.

One of the projects you may join focuses on developing an AI-powered system for extracting structured spatial data from 2D and 3D floor plan imagery. It is a practical, R&D-driven project involving room detection, layout extraction, area estimation, and solving real-world computer vision challenges such as perspective distortion, occlusion, and scale estimation.

The position can be either full-time or part-time, depending on the candidate’s level of expertise and relevant hands-on experience with similar CV/ML workflows.

🟠 Qualifications:

• 4+ years of hands-on experience in Computer Vision & Machine Learning.
• Strong practical experience with image segmentation, object detection, image preprocessing, and geometry-based computer vision.
• Experience with OpenCV and classical computer vision techniques.
• Experience with modern segmentation and detection architectures such as YOLO, U-Net, SegFormer, Detectron2, SAM, or similar.
• Strong Python engineering skills.
• Experience with polygon/vector processing tools such as Shapely, OpenCV contours, or similar geometry libraries.
• Ability to work with imperfect visual inputs and design robust fallback logic.
• Understanding of OCR-based extraction using tools such as Tesseract, PaddleOCR, docTR, or cloud OCR services.
• Ability to design end-to-end CV pipelines from experimentation to reproducible prototypes.

🟠 Would be a plus:

• Experience with floor plan recognition, architectural drawings, construction tech, real estate tech, or takeoff/estimation workflows.
• Experience with perspective correction, homography, depth estimation, vanishing lines, or top-down reconstruction.
• Experience with depth models such as MiDaS or Depth Anything.
• Experience with synthetic data generation or image-to-image normalization workflows.
• Experience building ML evaluation and observability pipelines.
• Experience integrating ML pipelines into backend services or APIs.
• Experience leading technical direction for R&D-heavy projects.

🟠 Responsibilities:

• Design and implement a render-to-plan pipeline for converting 3D floor plan renderings into simplified 2D measurement-ready layouts.
• Develop CV/ML approaches for room segmentation, boundary detection, polygon extraction, room classification, and space labeling.
• Work with complex visual inputs including top-down plans, oblique renders, dollhouse-style layouts, and low-quality marketing imagery.
• Estimate room-level areas using geometry, OCR, scale evidence, metadata, and heuristic-based validation approaches.
• Define evaluation logic, confidence scoring, and quality metrics for pipeline outputs.
• Produce structured outputs and visual QA overlays for downstream flooring takeoff workflows.
• Collaborate with AI/backend engineers to integrate the CV pipeline into a web-based PoC tool.
• Document technical assumptions, limitations, risks, tradeoffs, and fallback strategies.

🟠 Interview steps:

• Screening with the recruiter (about 45 minutes).
• Take-home task.
• Technical interview with ML/CV Engineer and PM (about 1 hour).

Vidar Systems is a Ukrainian startup in the field of acoustic technologies, operating at the intersection of defense and security. We develop acoustic systems that use sound to determine the location of hostile objects, including artillery and drones.

About the Role
Become a core member of our high-impact engineering team and architect the AI systems that protect Ukraine’s frontline defense. You will own the full lifecycle of ML solutions—from design to edge deployment—in a mission-critical acoustic reconnaissance environment.

What You’ll Do

• Design, implement, evaluate, and optimize ML/DL models for acoustic detection and classification tasks.
• Collect, clean, and preprocess datasets for model training and evaluation.
• Write modular, testable code for preprocessing, model inference, and automation tasks.
• Develop and maintain robust data pipelines to support efficient model training and evaluation workflows.
• Develop strategies for model quantization and compression to ensure high performance on resource-constrained hardware.

What You Need

• Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, or a related field.
• 2+ years of professional Python experience in ML/DL production applications.
• Hands-on expertise in designing, training, and integrating ML systems into production environments.
• Deep experience with TensorFlow, PyTorch, PyTorch Lightning, scikit-learn, NumPy, and Pandas.
• Strong analytical, communication, and problem-solving skills; ability to thrive and execute independently in a high-stakes, fast-paced startup environment.
• Good technical English.

Nice to Have

• C/C++ experience (especially valuable for our next-generation systems).
• Background in the audio domain or digital signal processing (DSP).
• Proficiency in training unsupervised learning models.
• Experience with the optimization and deployment of ML models on edge devices.

Our Recruitment Process

1. Intro call with recruiter — 45 min
2. Technical interview with ML Lead — 90 min
3. Test task — 4–6 hours
4. Final interview with ML Lead and CTO — 60 min

Why Join Us?

• High Autonomy: Shape the direction of our software solutions with minimal oversight and maximum ownership.
• Innovation at the Edge: Contribute to military acoustic reconnaissance systems at the forefront of defense tech, redefining ML in harsh, real-world acoustic environments.
• Flexible Work Options: Benefit from adaptable arrangements and a culture that truly values your input and well-being.

Svitla Systems Inc. is looking for a Senior MLOps Engineer with ML/AI for Azure for a full-time position (40 hours per week) in Ukraine. Our client is a leading global provider that gathers information and reports to enhance the environmental and social impacts on the business.

You’ll be part of a global team supporting multiple SaaS environments that help make the world a safer place. The team uses Azure as the core, but hosts on various platforms due to specific needs and the rapid pace of development and acquisition. The environment is rapidly shifting from IaaS to PaaS to serverless, with new AI/ML components integrated. So you’ll need to apply your current skill sets and learn new things daily to push the business forward. While you’ll ultimately need a diversity of expert-level skills to succeed, having a deep understanding and experience in just a couple of areas (monitoring, scripting, automation tools, etc.) may get you in the door to a great career.

Working hours with overlap till 8 PM UA time.
 

Requirements

• Solid experience designing, implementing, and managing infrastructure for AI/ML or HPC workloads.
• Proven success in managing and optimizing CI/CD for an Azure-based SaaS application.
• Hands-on experience with standard DevOps tools, including Azure DevOps.
• Expertise in scripting with at least PowerShell or Bash.
• Understanding of configuration management tools like Terraform.
• Proven experience designing, implementing, and managing infrastructure for AI/ML or HPC workloads.
• Working knowledge of version control/source code management tools.
• Experience working in an agile software development life cycle.
• Knowledge of databases, including SQL and NoSQL
• Strong knowledge of web server configuration and management, such as IIS or Tomcat.
• Familiarity with local and wide area networking and associated technologies, e.g., switches, routers, firewalls, VPNs.
• Strong understanding of security principles.
• Bachelor’s Degree in Computer Science or a similar area of study.
• Experience working in a technical, fast-paced environment with high demand and high standards.
• Ability to assimilate information quickly under pressure.
• Excellent communication and collaboration skills.
• Ability to communicate effectively with multiple disciplines.
• Excellent analytical skills with the ability to drive reliability improvements.
• Strong planning skills to ensure business expectations are met, and projects are delivered on time.
   

Nice to have

• Understanding of machine learning frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn, and their deployment in production environments.
• Familiarity with cloud-based networking (VNETs, NSGs, Route Tables, Hub/Spoke-based architecture, Private Endpoints, etc.).
• Strong understanding of CI/CD (YAML and Classic Pipelines).
• Experience with PaaS (Web Apps, Function Apps, Storage Accounts, Key Vaults, Azure Redis Cache, Azure Service Bus, API Management, Azure Data Factory, Azure Databricks).
• Experience in monitoring (New Relic, LogEntries, Rapid7, Azure Monitoring, etc).
• Some experience with containers/Docker, either for a microservice-based architecture or Service Oriented, etc.
• Familiarity with Git, ARM, Terraform, Ansible, Azure CLI, or similar.
   

Responsibilities

• Support application infrastructure to ensure the platform is optimized for performance and reliability.
• Build and maintain supporting infrastructure for cloud environments and applications.
• Lead the design and engineering of software systems for the AI/ML Platform, contributing to the full ML development life cycle.
• Identify and implement opportunities to automate and streamline ML development processes, fostering efficiency and effectiveness.
• Build and manage enterprise AI solutions using Azure AI Foundry & Azure's integrated platform (Azure OpenAI, AI Search, Prompt Flow),
• Use a wide range of Azure resources to implement scalable, reliable, and cost-efficient services.
• Work side by side with your engineers, guiding critical projects, using your subject matter expertise to solve complex problems.
• Perform and automate system administration services, including installation, configuration, maintenance, and disaster recovery
• Identify system-level issues related to OS configuration and virtual hardware bottlenecks.
• Provide automation, auditing, and other tooling for security, compliance, and resource usage. Monitor and improve processes for all deployments.
• Take ownership of operational excellence to establish and maintain business focused KPI's. Use these metrics not only as a basis for positive transformation, but also as a visible representation of your team's success.
• Maintain and take ownership of your tasks each sprint, ensuring time worked is logged, and details are added.
   

We offer

• US and EU projects based on advanced technologies.
• Competitive compensation based on skills and experience.
• Regular performance appraisals to support your growth.
• Flexibility in workspace, either remote or in one of our development offices.
• Comprehensive medical insurance, including dental and massages.
• Personalized learning program tailored to your interests and skill development.
• Sport reimbursement program for onsite and online activities.
• Bonuses for recommendations of new employees.
• Bonuses for article writing, public talks, and other activities.
• 20 vacation days, 10 national holidays and 5 sick leaves.
• Maternity leave policy and family days off.
• Free tech webinars and meetups organized by Svitla.
• Welcome and anniversary presents, gifts for children, and more.
• Regular corporate events and meetups.
• Awesome team, friendly and supportive community!

Competera uses Big Data and Deep Learning to change the way retailers do pricing. We are known for both: cutting-edge math ’under the hood’ and for deep expertise in the pricing domain. We are looking for an MLOps Engineer to develop the platform that supports the entire ML models lifecycle in production.

You could be a perfect match for the position if
You want to:
 

• Develop tools for Data Scientists that help them to scale in their operations and routines.
• Develop pricing algorithm/systems based on DS research; convert prototypes to robust systems for enterprise retailers.
• Build/optimize ML and mathematical algorithms. 
• Improve Data Scientists’ Dev Experience.
• Create/optimize data pipelines and systems for ML models.
• Optimize SDLC for ML models.
• Implement backend systems to expose ML systems for other platform components.

You have:

• Education in STEM-related fields, Computer Science/Math/Physics is preferable.
• Understanding of ML models training lifecycle.
• Python experience 5+ years.
• Ability to understand key ML principles and terms (loss, training loop, gradient descent, statistics, etc.).

You’re gonna love it, and here’s why:
 

• Rich innovative software stack, freedom to choose the best suitable technologies;
• Remote-first ideology: freedom to operate from the home office or any suitable coworking;
• Flexible working hours (we start from 8 to 11 am) and no time tracking systems on;
• Regular performance and compensation reviews;
• Recurrent 1-1s and measurable OKRs;
• In-depth onboarding with a clear success track;
• Competera covers 70% of your training/course fee;
• 20 vacation days, 15 days off, and up to one week of paid Christmas holidays;
• 20 business days of sick leave;
• Partial medical insurance coverage.

Drive innovations with us. Be a Competerian.

Why this matters

At Mojob, we are building a better way to connect the right talent with the right companies.

What began as a marketplace for small jobs has evolved into a modern hiring and staffing platform, used in production since 2019 across both public and private sectors. After years of product development, strategic decisions, and key pivots, we are now moving from foundation-building to scaling. AI will be critical to this next phase — and this is where you come in.

As Head of AI, you will lead and build production-grade AI capabilities that help redefine how people discover work and how companies find talent, at scale.

What you will be working on

AI is already part of our product: CV parsing, semantic skill matching, embedding pipelines, OpenAI based agents integrated with our core platform.

You’ll help shape what we build and how – evaluating our stack, recommending changes, and delivering high-impact capabilities like matching, screening, RAG-based support, and assistants, with a focus on quality, cost, and compliance in hiring.

• Design, build, and lead production AI features end-to-end: retrieval, ranking, summarisation, structured extraction, and agent workflows
• Own shared AI primitives – embeddings store, RAG services, evaluation harnesses – reused across multiple product areas
• Deliver high-impact capabilities such as talent–job similarity, explainable candidate
• screening, resume parsing to structured skills, support/knowledgebase Q&A, and job-description assistance
• Integrate AI capabilities into our services with clear APIs, observability, and per-tenant cost tracking
• Define and maintain evaluation suites, regression tests for prompts/retrieval, and monitoring for quality, latency, and cost
• Ensure responsible AI practices: explainability for scoring, audit logging, PII handling and bias awareness in hiring workflows
• Collaborate closely with product and engineering to ship MVPs in focused cycles and iterate based on real usage

Tech stack

• Python (Django) for backend services; Vue/Nuxt and Flutter for frontend applications
• AWS, Kubernetes
• PostgreSQL (with pgvector), Elasticsearch, Redis
• Celery for asynchronous task processing

We believe in pragmatic engineering — with a focus on safety and quality, shipping quickly what delivers value, learning fast, and iterating from there.

What we are looking for:

Required experience

• Strong software engineering experience building production systems
• Solid SQL/PostgreSQL and API design experience
• Demonstrable experience shipping LLM-based features used by real customers, including RAG, embeddings, vector search, and structured LLM outputs
• Experience building evaluation and monitoring for AI systems (golden sets, regression tests, cost/latency telemetry)
• Understanding of multi-tenant SaaS, async workers (e.g. Celery), and production incident response
• Familiarity with cloud platforms (preferably AWS) and modern observability tooling
• Strong communication skills and fluent in English

Highly valued

• OpenAI APIs, Agents SDK, LangChain, or similar agent/orchestration frameworks
• pgvector, Pinecone, or other vector databases; hybrid search with Elasticsearch
• HR tech, marketplaces, or other domains with compliance and high-stakes decisions
• Document understanding (CV/resume parsing) and conversational assistants
• Pragmatic MLOps: feature flags, prompt versioning, shadow deployments
• Experience with fine-tuning or adapting models (e.g. OpenAI fine-tuning, LoRA, domain adapters) when retrieval and prompting are insufficient — including eval before/after and safe rollout
• Awareness of the EU AI Act and its implications for HR/hiring systems (risk classification, transparency, human oversight, documentation)

Personal qualities

• Strong systems thinking and delivery focus: You finish what you start
• Pragmatic: You balance innovation with stability, cost, and user trust
• Strong communicator and collaborator: You are able to work in diverse teams and build systems from the ground up
• Curious and discerning: You’re in the know and can separate hype from reality, and measure what matters
• Ownership in a small team: You take end-to-end responsibility for your work — from idea and design through delivery, monitoring, and follow-up — without waiting to be assigned every step
• Proactive problem solver: You take initiative, spots gaps, risks, and blockers early, and drive work forward in a team of ~10 (with 2-3 people focused on AI)

We value openness, collaboration, and an enjoyable work environment.

What we offer

• High trust and ownership
• Meaningful product impact on a platform in growth
• Autonomy to shape AI architecture and delivery practices
• Remote work or hybrid work from our Oslo office
• Collaborative, sharing and diverse team
• Competitive compensation and opportunity to grow with Mojob’s AI roadmap

We are looking for a Senior AI/ML Engineer experienced in multimodal AI pipelines, LLM evaluation frameworks, agent orchestration, and scalable Python backend systems on AWS.

A Korean company is building and hardening an AI verification and compliance layer for AIGC/UGC financial content.

The system includes:

• four evaluation/verification models
• an automated compliance rule engine
• a Trust & Safety moderation pipeline

The core architecture processes video-based content through a multi-stage pipeline:

STT → OCR → image/video analysis → financial rules engine → LLM-based decision layer

Final output decision types:

• Auto-Block
• Auto-Pass
• Human Review

This role requires strong production engineering skills combined with hands-on experience in multimodal LLM evaluation systems.

Required Skills & Experience

• Multimodal LLM evaluation pipeline design
  (LLM-as-a-judge, rubric-based scoring, prompt/few-shot optimization, schema design, agent orchestration)
• Model evaluation engineering
  (golden dataset creation, metric definition: precision/recall/human agreement, A/B testing, benchmarking automation)
• AI serving & inference optimization
  (AWS Bedrock integration, vLLM / GPU inference, latency optimization, cost-aware design, fallback strategies)
• Strong Python backend engineering (~7–10 years)
  (async systems, queues, microservices, service-oriented architecture)
• Trust & Safety / compliance systems
  (rule engines: keyword + context IF-THEN logic, moderation workflows, HITL queues, severity-based escalation)

Nice to Have

• Experience fine-tuning or improving LLM / video understanding models
• Background in content moderation or compliance systems
• Experience with Korean language content processing
  (STT, OCR optimization, NSFW detection pipelines)

Tech Stack

Languages / APIs: Python (FastAPI), React (TypeScript)
LLM / Multimodal: AWS Bedrock, VLMs (e.g. Qwen2.5-Omni), vLLM
Agent frameworks: LangGraph, CrewAI, Google ADK, LangChain
Evaluation: LLM-as-judge, rubric scoring, DeepEval-style eval harnesses
Cloud / Infra: AWS Bedrock, SageMaker, RDS (PostgreSQL), S3, EKS
Observability: Langfuse, prompt testing & tracing tools
Data platform: Databricks
Media processing: Whisper, OCR pipelines, image moderation tools (e.g. AWS Rekognition)

👋 Hey! We are Kultprosvet — a team of passionate web and mobile developers who build meaningful products with care.
We’re expanding and looking for an experienced Senior Computer Vision Engineer to join our team and take ownership of the AI/ML direction in one of our key products.

📸 About the Project:

Our platform empowers photographers by combining beautiful online galleries, smart automation, and eCommerce tools.
Through the power of AI and machine learning, we automate image recognition, enhance visuals, and unlock new business potential for creatives worldwide.

You’ll be working on the core AI layer of a high-impact real-world product used by professional photographers and their clients.

✅ Requirements:

• Source Code Management
• Solid understanding of data structures, data science techniques, and algorithms
• Experience with Python and data processing tools (SciPy, NumPy, Pandas, etc.)
• Experience with ML model creation in PyTorch
• Experience with the development of APIs for ML models
• Upper-Intermediate English speaking skills

➕ Nice to Have:

• Experience with modern AI techniques such as transformers and contrastive pretraining

You will:

• Creating AI/ML-based algorithms for computer vision tasks
• Building and maintaining the infrastructure for data and model management
• Organizing ML model training

• Integrating AI/ML-based services with the project

   

🎁 What We Offer:

🏡 Flexible work setup — remote or from our office in Dnipro.
💰 Senior-level compensation, paid vacations, and sick leave.
🩺 Medical insurance and full accounting support.
📚 Budget for courses, conferences, and professional development.
🧠 Coverage for psychotherapy sessions — your well-being matters.

💡 If you’re ready to take full ownership of CV/ML in a fast-moving, high-impact product — let’s talk! 🚀

Who we are:

Adaptiq is a technology hub specializing in building, scaling, and supporting R&D teams for high-end, fast-growing product companies in a wide range of industries.

About the Product:

We are building an AI-first platform that fuses multiple maritime data sources into a unified operational picture. The system builds a digital twin of global maritime activity, applies behavioral analytics and predictive AI models to surface smuggling, illegal fishing, container risk, and other compliance or security threats, and presents mission-grade intelligence to both commercial and government stakeholders. 

Operating at global scale, the platform processes millions of events and terabytes of geospatial data daily, relies on cloud infrastructure and microservices, and integrates with upstream research prototypes from data science teams.

About the Role:

As a Senior MLOps Platform Engineer, you will be the driving force behind scaling AI capabilities by owning end-to-end infrastructure and processes supporting the full lifecycle of ML models. You will collaborate closely with data scientists, data analysts, and platform engineers to design and build systems for dataset and label management, model registry, experiment tracking, and model serving. 

Your contributions will enable faster, more reliable model deployments and deliver measurable impact in a mission-critical AI platform.

Key Responsibilities:

• Design and implement systems for dataset and label management, including versioning and customer feedback integration.
• Establish and maintain a model repository/registry with version control, lineage tracking, and local inference support.
• Lead implementation of experiment tracking and monitoring solutions for data science and generative AI, focusing on evaluation, drift detection, and reproducibility.
• Lead the deployment, lifecycle management, and continuous improvement of ML/DL models in production.
• Own model serving and inference infrastructure, including autoscaling, A/B testing, canary deployments, and latency/cost optimization.
• Enable generative AI capabilities by developing tagging tools, prompt management services, and LLM testing frameworks.
• Drive operational excellence by improving tool deployment usability and establishing granular cost visibility across environments and projects.
• Develop reusable components such as standardized data loaders, CI/CD pipelines, and automated model retraining workflows.
• Collaborate with data scientists and platform engineers to productionize ML/DL models in public cloud environments.

Required Competence and Skills:

• At least 5+ years of hands-on experience in MLOps / ML Platform Engineering (or equivalent ML Engineering experience with strong MLOps ownership). Able to independently design, build, and scale production ML infrastructure.
• Experience collaborating closely with Data Scientists or ML Research teams to productionize machine learning models.
• Strong Python programming skills.
• Hands-on experience in containerization, CI/CD, and public cloud platforms (AWS, Azure, or GCP) for deploying, serving, and monitoring ML models.
• Proficiency with dataset management, model versioning, experiment tracking, monitoring, and MLOps platforms (e.g. MLflow, SageMaker, or similar tools).
• Experience with machine learning frameworks (PyTorch or TensorFlow), big-data technologies (Apache Spark), and data stores such as PostgreSQL, MongoDB, and Redis.
• Experience using AI-assisted development tools and adopting Generative AI and agentic workflows in day-to-day software development.
• B.Sc. or M.Sc. in Computer Science, Software Engineering, or a related field.

Nice to Have:

• Java programming experience in production environments.

We're looking for a senior backend engineer to own their new customer-facing API and AI services from architecture through production.

This is a high-autonomy role. You'll work directly with the founders on architectural decisions and own implementation end to end. Greenfield build, not maintenance.

What you'll own

• API development - lead a new external API end to end: OpenAPI design, framework and hosting decisions, and optimized SQL powering dynamic filtering.
• AI microservices - build and deploy agentic services that turn natural-language queries into deterministic, auditable filters. Customer-scoped auth, evaluation, and deterministic validation are core, not afterthoughts.
• Workflow builder - help design and build an n8n-style automation product: schema, execution model, scheduling, retries, persistence, and integrations.
•  

What we're looking for

• Strong backend experience building production systems from scratch
• Python or TypeScript/Node.js, plus solid SQL and Postgres
• Designing APIs, data models, and distributed jobs with auth, idempotency, retries, and observability
• Practical experience with LLM-backed systems - agentic frameworks, RAG, structured outputs, evaluations, and deterministic validation
• Comfortable using AI tooling (Claude, Codex) to ship maintainable, modular systems without sacrificing quality
• Deployed production systems on cloud (GCP preferred; AWS/Azure fine)
• Clear product judgment and communication in ambiguous, fast-moving work
•  

Nice to have

• GCP services (Cloud Run), Supabase, Vercel, Clerk, Stripe
• Search, entity resolution, workflow engines, or complex data products
• Open-source LLMs

• React/Next.js to ship customer-facing flows (this role is backend-first, not front-end)

   

How we work

Full-time, long-term engagement. Remote, with meaningful daily overlap with US hours. AI-first team; daily standups early, lighter check-ins once the rhythm is set. Strong judgment and ownership matter more than knowing every tool in the stack.

Stack: Python / TypeScript · Postgres (Supabase) · GCP (Cloud Run) · LLM / agentic services · MCP

Mirko Solutions is an international IT company specializing in web and mobile development for clients across the US, Canada, EU, and Australia. We are growing rapidly and are looking for a Middle\Senior AI Engineer to join our team and drive complex, high-impact projects.

Job Requirements:

• 3+ years of experience deploying machine learning models (classical ML and/or LLMs) in cloud environments (AWS/GCP/Azure) using containers and Kubernetes
• Hands-on experience with MLOps tools such as MLflow, Kubeflow, SageMaker, Vertex AI, Feast, or equivalent
• Proven experience building robust data/feature pipelines and implementing monitoring for model drift and performance
• Strong Software Engineering fundamentals: version control, automated testing, CI/CD, security, and cost-aware development
• Excellent collaboration and communication skills in  English 
• Ownership mindset, curiosity, and a bias for action in a fast-paced environment

Responsibilities:

• Design, implement, and maintain end-to-end ML pipelines for both classical ML and LLM-based solutions
• Deploy and manage models in cloud environments (AWS / GCP / Azure) using containers and Kubernetes
• Apply MLOps best practices for reproducibility, automation, and monitoring
• Build reliable data/feature pipelines and implement real-time monitoring for model drift, latency, and performance tracking
• Actively contribute to engineering excellence through CI/CD, testing, security, and cost optimization

Nice to have:

• Experience with deep learning frameworks such as PyTorch or TensorFlow
• Understanding of distributed systems (Spark, Ray)
• Experience working with feature stores and data governance

We provide the following for our employees:

• Competitive salary according to qualification
• Comfortable working environment
• Experienced colleagues
• Opportunity to work with interesting projects,
• Regular performance reviews
• Friendly atmosphere, care for the comfort of professionals

We are a Ukrainian DefenseTech company developing cutting-edge solutions for Unmanned Ground Vehicles (UGVs). Our team brings together experts in Robotics and AI, including ex-Google engineers and professionals with international DeepTech experience. We tackle complex engineering challenges in environments where any failure comes at a high cost. We are looking for an engineer to develop a new product currently in the R&D stage and actively undergoing field testing in Ukraine.

What you'll do

• Develop and improve computer vision and autonomous navigation algorithms
• Build and optimize CV pipelines for real-time operation
• Optimize model inference for edge compute hardware
• Design and run tests — from simulation through to real hardware in the field
• Integrate software components with hardware platforms

• Contribute to sensor and camera selection and system architecture decisions alongside the team

   

What we need from you

• Python and C++ at production level
• ROS / ROS2: building and maintaining nodes, system debugging
• Computer vision pipeline: OpenCV, real-time video, stereo processing, depth estimation
• SLAM experience — ORB-SLAM, RTAB-Map, OpenVINS, or equivalent
• Experience with autonomous platform control systems (ArduPilot, PX4, or equivalent)
• Model deployment on edge hardware (Jetson, RPi, or equivalent)

• Comfortable with real hardware: sensor calibration, field debugging

   

Nice to have

• Experience with thermal or depth cameras
• Object detection / segmentation and custom training pipelines
• Experience with simulation environments (Webots, Gazebo, AirSim, or equivalent)
• Background working with UGV or UAV platforms

• Experience in defense or dual-use robotics

   

What we offer

• Meaningful and high-impact work in the ground defence domain
• Practical R&D environment with a high level of autonomy
• Direct influence on technical decisions and product direction
• Collaboration with an experienced senior engineering team
• Clear and efficient senior-to-senior communication with a minimum number of meetings
• Remote, hybrid, or office-based work format
• Office in the center of Kyiv