Jobs ML / AI

Requirements

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Applied Mathematics, or related field.
• 7+ years of experience in data science or machine learning roles, ideally with exposure to healthcare projects.
• Strong knowledge of ML frameworks such as scikit-learn, TensorFlow, PyTorch, XGBoost, or LightGBM.
• Proficiency in Python for data science and related libraries (NumPy, pandas, matplotlib, seaborn, etc.).
• Experience working with large datasets and data processing frameworks (e.g., Spark, Dask, SQL).
• Understanding of MLOps concepts and tools (e.g., MLflow, Kubeflow, Vertex AI, Azure ML).
• Familiarity with cloud environments (Azure, AWS, or GCP) for training and deploying models.
• Experience with model interpretability, fairness, and explainability techniques.
• Strong communication and visualization skills for storytelling with data.
• English proficiency at Upper-Intermediate level or higher.

Preferred Qualifications (Nice to Have)

• Experience working with medical data (EHR, imaging, wearables, clinical trials, etc.).
• Familiarity with healthcare regulations related to data and AI (e.g., HIPAA, GDPR, FDA AI/ML guidelines).
• Knowledge of FHIR, HL7, or other healthcare interoperability standards.
• Practical experience with deep learning models (e.g., CNNs for imaging, transformers for NLP).
• Involvement in presales, proposal writing, or technical advisory work.

Job responsibilities

• Lead the design and development of AI/ML solutions across HealthTech and MedTech projects.
• Participate in technical presales by analyzing business cases and identifying opportunities for AI/ML application.
• Build and validate predictive models, classification systems, NLP workflows, and optimization algorithms.
• Collaborate with software engineers, cloud architects, and QA to integrate models into scalable production systems.
• Define and guide data acquisition, preprocessing, labeling, and augmentation strategies.
• Contribute to the development of GlobalLogic’s healthcare-focused AI accelerators and reusable components.
• Present technical solutions to clients, both business and technical audiences.
• Support model monitoring, drift detection, and retraining pipelines in deployed systems.
• Ensure adherence to privacy, security, and compliance standards for data and AI usage.
• Author clear documentation and contribute to knowledge sharing within the Architects Team.

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 Middle/Senior ML Engineer to turn loosely framed business problems into reliable, actionable models for a proprietary trading platform that connects traders with funding opportunities. You will work in a high-load, low-latency environment processing millions of events in real time, taking ownership from problem framing and feature engineering through model testing and business-ready results.

Required for this role

• Solid grounding in machine learning theory, with the ability to explain and justify modeling decisions beyond library calls.
• Hands-on experience with Python, NumPy, SciPy, Pandas, and Scikit-learn.
• Experience working with PySpark, including MLlib, for data processing and machine learning.
• Practical experience with XGBoost or other gradient boosting methods (GBM).
• Understanding of logistic regression and its practical application to business problems.
• Experience with survival analysis or time-to-event modeling.
• Knowledge of hierarchical modeling methods and when to apply them.
• Experience using MLflow or comparable experiment and model tracking tools.
• Ability to independently frame a problem from rough context, engineer features, build and test models, and translate results into actions the business can use.
• Strong communication and comfort with ambiguity, including asking questions and flagging unclear assumptions early.

Nice to have

• Familiarity with Microsoft Fabric.

Your responsibilities

• Take loosely framed business problems and develop appropriate ML solutions from scratch.
• Explore data, test hypotheses, and iterate on potential approaches in notebooks.
• Engineer features and build models using gradient boosting, logistic regression, survival analysis, or hierarchical methods, depending on the problem.
• Select rigorous, relevant evaluation metrics based on the business objective and modeling approach.
• Validate whether models hold up against the available data and intended use case.
• Translate experimental findings and model results into clear, actionable outcomes for the business.
• Challenge problem framing when assumptions do not hold, and communicate questions, risks, or blockers early.

What you get

Your time off

• 18 paid vacation days and 10 paid sick days annually
• 10 Ukrainian public holidays
• Maternity and paternity leaves
• Marriage and Parenthood Package
• Additional leave for major life events
• Sabbatical leave opportunities

Learning & growth

• Sombra University workshops and internal learning programs
• Tech Communities and knowledge sharing sessions
• Language courses and workshops
• Mentorship opportunities

Health & well-being

• Sports compensation or health insurance coverage
• Participation in races and marathons
• Corporate doctor (telemedicine)
• Well-being initiatives and workshops

And even more

• Company-provided technical equipment
• PE administration and tax support
• Internal referral program
• IT Club loyalty program
• Company events and volunteering initiatives

Before you apply

Our recruitment team will carefully review your profile, and if we see a good match with the role, we’ll reach out to you shortly.

If you don’t hear from us within 5 business days, it means we’ve decided to continue the process with other candidates for this position. Thanks for understanding.

Summary

• Senior AI/ML Engineer with extensive experience deploying machine learning models on cloud platforms including GCP, AWS, and Azure.
• Experienced in Python and ML frameworks such as TensorFlow, PyTorch, and scikit-learn.
• CI/CD pipelines and managing ML workflows: Kubeflow and VertexAI.
• Background in data processing with Apache Beam/Dataflow and expertise in model monitoring, performance optimization, and scaling.
• Ability to collaborate cross-functionally to deliver AI-driven solutions in production environments.

Location: Poland, Romania, Bulgaria, Czech Republic, Slovakia.

• Location: Poland - B2B Only
• Romania - COE or B2B,
• Bulgaria: COE / B2B,
• Czech Republic - CEO
• Slovakia - COE

Role Overview:

The Senior Artificial Intelligence/Machine Learning Engineer is a key member of the MLOps team within a cross-functional development environment. This role involves close collaboration with data scientists, software engineers, and other stakeholders to operationalize machine learning models by deploying, maintaining, and monitoring them efficiently in production. The engineer contributes to enhancing model performance and infrastructure, supporting AI-driven solutions that address complex business challenges.

Responsibilities:

• Model Deployment: Collaborate with data scientists to transition machine learning models from development to production, ensuring high performance and scalability.
• Build Pipelines: Develop and maintain data and model pipelines that integrate seamlessly with existing systems to support reliable and efficient workflows.
• CI/CD for ML: Design and implement continuous integration and delivery pipelines to streamline the deployment process of machine learning models.
• Model Monitoring: Monitor the performance of deployed machine learning models to ensure reliability, scalability, and quality over time.
• Collaboration: Work with cross-functional teams to design solutions that meet business needs while adhering to best practices in machine learning and software engineering.
• Optimization: Continuously improve infrastructure to maintain cutting-edge AI model production and delivery capabilities.

Technologies and Tools:

• Cloud platforms: Google Cloud Platform (GCP), Amazon Web Services (AWS), Microsoft Azure
• CI/CD tools: GitHub Actions, Docker
• ML platforms/frameworks: VertexAI (Enterprise Agent Platform), Kubeflow, SageMaker
• Data processing frameworks: Apache Beam, Dataflow (highly desirable)
• Programming languages and libraries: Python, TensorFlow, PyTorch, scikit-learn

Key Skills and Competencies:

• Strong foundation in both machine learning and software engineering
• Experience deploying machine learning models in production environments
• Expertise in building and maintaining CI/CD pipelines for ML
• Knowledge of monitoring and maintaining models post-deployment
• Problem-solving and troubleshooting skills related to models and pipelines
• Performance and cost optimization experience (e.g., latency, throughput) is highly desirable
• Excellent communication skills for effective cross-team collaboration

Technologies: Cloud platforms (GCP, AWS, Azure), VertexAI, Kubeflow, SageMaker, Python, TensorFlow, PyTorch, scikit-learn, Apache Beam, Dataflow, Docker, CI/CD, GitHub Actions.

We are looking for a highly organized and detail-oriented AI Image Editing & Back Office Specialist to join our team.
 

This role combines AI-powered image editing with operational back-office support. You will receive requests through our help desk system, process AI image edits, and ensure every request is completed accurately and assigned to the correct ticket.
 

Success in this role depends on attention to detail, strong organizational skills, and the ability to manage a high volume of requests without mistakes.
 

Responsibilities

• Edit static images using AI face swap and image editing tools.
• Process requests received through the internal help desk system.
• Prepare edited images and return them to the appropriate support ticket.
• Maintain accuracy and consistency across all requests.
• Handle multiple tasks simultaneously while following established workflows.
• Perform back-office tasks within internal systems.
• Ensure all requests are completed correctly and on time.
 

Requirements

• Experience using AI tools for editing static images and face swaps.
• Strong attention to detail and excellent organizational skills.
• Previous experience with back-office or operational support.
• Comfortable working with ticketing/help desk systems.
• Ability to manage a high volume of repetitive tasks while maintaining accuracy.
• Self-motivated and able to work independently.
 

Nice to Have

• Experience with tools such as FaceFusion, Roop, InsightFace, ComfyUI, Stable Diffusion, Flux, Photoshop AI, or similar AI image editing software.
• Experience working in customer support platforms or help desk systems.
• Experience with workflow automation.
 

What We Offer

• Remote full-time position.
• Comprehensive salary
• Long-term opportunity.
• Work with modern AI technologies.

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.

We’re looking for an AI Automation Engineer to build and launch an automated video production pipeline for Counter-Strike 2 content.

The goal is to automate the full workflow for YouTube Shorts, Instagram Reels, and TikTok — from content sourcing and AI processing to editing, voice-over, subtitles, publishing, and performance tracking.

Responsibilities

• Design and build an end-to-end video automation pipeline from scratch;
• Build complex n8n workflows with schedules, queues, conditions, parallel branches, retries, and error handling;
• Integrate LLMs and AI APIs such as OpenAI, Anthropic, and others;
• Integrate video generation, processing, and editing services via API;
• Automate AI avatars, lipsync, voice-over, dubbing, and character modifications;
• Automate video editing: different sources, scenes, hooks, subtitles, and voice-over;
• Set up scheduled publishing via YouTube Data API, Instagram Graph API, and other platform APIs;
• Work with OAuth, multiple accounts, API limits, and logging;
• Implement automated pre-publish checks: descriptions, hashtags, stop-lists, and AI-content labels;
• Build an operator dashboard for content calendar, queues, errors, providers, and content types;
• Collect performance metrics and optimize content distribution based on results;
• Monitor, troubleshoot, and scale the pipeline to new platforms and channels;
• Maintain technical documentation: README, ARCHITECTURE, RUNBOOK.

Requirements

• Hands-on experience building automation workflows / pipelines from scratch;
• Strong n8n experience with complex production workflows;
• Knowledge of Python or JavaScript for custom scripts;
• Experience with REST APIs, Webhooks, and OAuth;
• Experience integrating LLMs / AI APIs such as OpenAI or Anthropic;
• Experience with video generation, processing, or editing APIs;
• Experience with social media publishing APIs such as YouTube API / Instagram Graph API;
• Ability to independently break down a task, choose the right tools, build the solution, and bring it to stable production;
• English sufficient for reading technical documentation.

Nice to have

• Experience with AI content generation pipelines;
• Experience with FFmpeg or similar video-processing tools;
• Experience with AI avatars, lipsync, TTS/STT, voice cloning, or dubbing;
• Experience automating TikTok, Reels, or YouTube Shorts;
• Experience with Zapier, Make (Integromat), or similar automation tools;
• Understanding of monitoring, logging, queues, and fault-tolerant workflows.

What We Value

We’re looking for someone who can own the entire automation flow — from architecture and tool selection to MVP, production launch, optimization, and scaling.

We value autonomy, ownership, and a result-oriented mindset.

And if you play CS2 / CS, that’s an extra bonus — we also run internal CS2 tournaments 🎮

AI courses for business people — from beginner to advanced — in English.

Duties

• Write lesson scripts that are clear, practical and enjoyable to read — no theory for theory's sake.
• Create the visuals: diagrams, AI-generated illustrations, annotated screenshots.
• Script and produce videos: click-by-click screen tutorials and narrated lesson videos (HeyGen, Synthesia or similar).
• Design practice assignments, self-check questions and a capstone project for each course.
• Test every prompt and tool step before it ships; keep content 100% original and free of unsourced statistics.
• Revise quickly on founder feedback.

Requirements: daily user of ChatGPT, Claude, Gemini and image tools; native-level English; portfolio with at least one course or five lessons and one video you produced yourself.

Terms: paid per module, first module is a paid pilot, start immediately.

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.

Turn your curiosity for automation and AI into a technology career. 

We are looking for self-driven professionals from Assurance who have demonstrated a passion for improving the way work gets done through Python, automation, data analytics, Copilot, or Generative AI. Whether you have built scripts, automated repetitive tasks, experimented with AI tools, or simply enjoy exploring new technologies, this role offers an opportunity to transform that passion into a full-time technology career. 

As a Junior AI Engineer, you will learn how to design and develop scalable AI-powered solutions while combining your audit and business knowledge with modern engineering practices. Working alongside experienced AI engineers, you will gain hands-on experience with Python, Generative AI, cloud platforms, intelligent automation, and enterprise AI solutions. 

This is a career opportunity for professionals who want to evolve from being consumers of technology into creators of technology, helping shape how AI is used across PwC and for our clients. While previous AI engineering experience is not required, a genuine interest in technology, continuous learning, and hands-on experimentation is essential. 

Key Responsibilities 

AI Solution Development:

• Develop AI and automation solutions using Python. 
• Build and maintain integrations with LLM APIs and AI services.
• Support implementation of RAG-based applications.
• Assist in developing prompt engineering strategies and reusable AI components.
• Participate in testing, debugging, and improving AI solutions. 

Engineering Excellence:

• Write clean, maintainable, and well-documented code.
• Participate in code reviews and technical discussions.
• Create and maintain REST APIs and backend services.
• Support CI/CD pipelines and deployment activities.
• Follow secure coding and software engineering best practices. 

Data & AI Operations:

• Prepare and process structured and unstructured data.
• Assist with document processing, OCR, chunking, and embedding pipelines.
• Work with SQL and vector databases.
• Monitor AI solution performance and troubleshoot production issues. 

Learning & Innovation: 

• Continuously learn emerging AI technologies and frameworks.
• Contribute to internal proof-of-concepts and AI adoption initiatives.
• Share knowledge with the broader AI engineering community. 

Required Qualifications 

Technical Skills: 

• 1–3 years of experience in software development or automation.
• Good Python programming skills.
• Understanding of object-oriented programming and software engineering principles.
• Experience working with APIs and JSON data structures.
• Basic knowledge of Git and version control workflows.
• Understanding of relational databases and SQL.
• Familiariaty with cloud concepts (Azure preferred).
• Interest in Artificial Intelligence and Generative AI technologies. 

AI Knowledge:

• Experience using AI IDEs (Cursor/Copilot/Claude/and so on) during daily work.
• Basic understanding of:  Large Language Models (LLMs), Prompt Engineering, Embeddings, RAG concepts, Vector search fundamentals.

Nice-to-Have Skills

• LangChain, LangGraph, CrewAI, Semantic Kernel 
• Azure AI services
• Azure AI Search
• Azure Document Intelligence
• Azure AI Foundry
• FastAPI or Flask
• Docker containers
• Kubernetes basics
• Vector databases (Qdrant, pg_vector, Azure AI Search)
• Async Python programming
• Event-driven architectures and messaging systems
• Pandas and data processing libraries
• GitHub Actions or Azure DevOps pipelines 

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

We are looking for a Senior AI / Machine Learning Engineer with a strong software engineering and backend development background.

Full-time | Remote | Long-term engagment

Start: ASAP

Candidate location: EU

This is a hands-on engineering role combining Machine Learning, LLMs, backend development, and MLOps. We are looking for someone who can take an AI/ML use case, build the required solution in Python, integrate it with existing services and workflows, and make sure it can be run, tested, and maintained in a production environment.

The ideal candidate has strong experience with Python and backend development, a solid understanding of Machine Learning, and practical experience working with LLM-based solutions. Experience with AWS is required, while knowledge of Docker, Kubernetes, and MLOps is important for working effectively with the existing engineering and platform teams.

Our current focus is increasingly moving towards LLM-powered solutions. We are particularly interested in engineers who have practical experience integrating LLMs into real applications and business workflows. Experience with technologies such as OpenAI, AWS Bedrock, or Google Gemini is highly relevant, as well as experience with RAG, embeddings, model adaptation, or fine-tuning.

At the same time, this is not a research-focused or prompt-engineering role. We need someone with strong engineering skills who can build the backend and internal services around AI capabilities. Experience with APIs, databases, asynchronous processing, authentication/authorization, and writing maintainable production code is important.

You should also have a good understanding of MLOps and the ML lifecycle, including how models and AI services are developed, tested, deployed, monitored, and maintained. Hands-on experience with Docker and basic Kubernetes knowledge is expected.

Deep DevOps expertise is not required. Our Application Platform Team is responsible for most of the infrastructure and production deployment. However, you should be comfortable working with cloud-based environments, understand the principles behind MLOps, and be able to independently run and test your solution locally using the appropriate development and containerization tools.

Experience with AWS is essential. Experience with services such as SageMaker is useful, particularly for traditional ML use cases, although the main focus of the team is now shifting towards LLM-based applications.

Experience building AI agents is not a requirement. What matters most is practical experience using LLMs as part of existing applications, internal services, and business processes.

Key requirements

Strong Python and software engineering skills

Significant backend development experience

Experience building APIs and internal services

Solid understanding of Machine Learning and ML model lifecycle

Practical experience with LLMs / Generative AI

Experience integrating LLMs into applications and workflows

Strong AWS experience

Understanding of MLOps

Experience with Docker and basic Kubernetes

Experience working with databases

Understanding of asynchronous programming and concurrency

Experience with authentication and authorization

Ability to run, deploy, and test solutions locally

Experience with OpenAI, AWS Bedrock, or Google Gemini

RAG and vector search

Embeddings

LLM evaluation and optimization

Fine-tuning / adapting foundation models

LangChain or LangGraph

MLflow, Kubeflow, SageMaker

Kafka, Redis, or similar distributed systems technologies

Location: Europe only
Employment type: Full-time, Remote
 

About the Role

We're looking for a Middle/Senior Generative AI / Machine Learning Engineer to help build production-grade AI systems from classical ML and deep learning models to modern LLM-powered applications. 
You'll work across the full lifecycle: designing and training models, building RAG and agentic pipelines, and deploying everything into scalable, well-architected production systems.

This role blends hands-on ML engineering with GenAI/LLM development, MLOps, and data engineering, ideal for someone who enjoys working across the stack rather than staying in one narrow lane.
 

What You'll Do

• Design, train, and deploy classical ML and deep learning models (PyTorch, TensorFlow/Keras, scikit-learn) for tasks such as time series analysis, anomaly detection, forecasting, and optimization.
• Build production LLM applications: RAG pipelines, embeddings, semantic search, document processing, and chunking strategies.
• Develop AI agents and multi-step workflows using LangChain, LangGraph, and MCP (Model Context Protocol).
• Apply prompt engineering best practices to improve reliability and output quality of LLM-based systems.
• Deploy and serve models using Docker, Kubernetes, and FastAPI/Flask.
• Build and maintain data pipelines (ETL/ELT) using Apache Airflow, Spark/Databricks, and BigQuery, with a focus on data quality.
• Contribute to system architecture decisions — applying principles like Domain-Driven Design, event-driven architecture, and microservices to build highly available, distributed systems.
• Work with cloud infrastructure, primarily Azure (AWS experience is a plus); experience with Azure OpenAI is a strong advantage.
   

What We're Looking For

Core:

• Strong Python skills with solid experience in classical ML and deep learning (PyTorch, TensorFlow/Keras, scikit-learn).

GenAI / LLM:

• Hands-on experience building production LLM applications: RAG, embeddings, chunking, semantic search, document processing.
• Experience with LangChain, LangGraph, AI agents, and MCP (Model Context Protocol).
• Solid understanding of prompt engineering.

Machine Learning / Data Science:

• Experience with deep learning and classical ML techniques applied to time series, anomaly detection, forecasting, and optimization problems.

MLOps / Deployment:

• Experience with Docker, Kubernetes, and model serving via FastAPI or Flask.

Data Engineering:

• Experience with ETL/ELT processes, Apache Airflow, Spark/Databricks, BigQuery, and building reliable data pipelines with strong data quality practices.

Cloud:

• Experience with Azure (preferred); AWS experience is a plus. Experience with Azure OpenAI is an advantage.

Architecture / System Design:

• Familiarity with architecture frameworks and practices such as TOGAF, C4, ArchiMate, Domain-Driven Design, event-driven architecture, high availability, distributed systems, and microservices.

We offer:

• Remote Work Environment. Work from anywhere and be part of a geographically diverse team;
• Stay Ahead of the Curve. Work with cutting-edge technologies;
• Possibility to influence on processes;
• Paid 16 vacations and 14 sick leaves per year;
• Flexible working hours;
• Possibility of payment by FOP, or Payoneer/Wise;
• Compensation program for purchasing new laptops;
• Paid professional certifications & educational courses;
• Paid English classes;
• Friendly atmosphere with quarterly team buildings;
• No bureaucracy.
   

We respect your time, so inform in advance that the hiring process includes a 2-step interview:

• General interview
• Technical interview

Please note that a background check (reference check) is a mandatory stage of our interview process for this role.
 

Ready to try your hand? Do not pull the cat’s tail and send your CV without a doubt!

For those candidates who don’t get any feedback after applying: We are so thankful for your time and attention to our vacancy! However, sometimes we get too many CVs at once, and it would take several days to answer them all. That’s why we reach out only to relevant candidates. We hope for your understanding.

About the role:
We’re looking for a GenAI Engineer to design and build production-grade AI capabilities, including intelligent agents, LLM-powered features, and workflow automation. In this role, you’ll collaborate closely with product, engineering, and design teams to integrate cutting-edge AI technologies into a large-scale, customer-facing product.

You’ll join a US-based team developing one of the world’s leading enterprise video platforms, used by thousands of organizations worldwide for live streaming, virtual events, online training, webinars, and other interactive experiences.
Requirements:

• Strong software engineering background (Python preferred)
• Proven track record of building production-grade GenAI applications
• Hands-on experience with LLMs, RAG, AI agents, vector databases, and AI orchestration frameworks
• Practical experience with OpenAI, Anthropic, Google Gemini, Amazon Bedrock, or similar AI platforms
• Strong system design and problem-solving skills
• Upper-Intermediate English (B2+) or higher 

Nice to Have

• Experience with AWS and cloud-native applications
• Exposure to MCP, AI automation, or multimodal AI 

Responsibilities

• Build AI-powered features using modern LLMs
• Develop AI agents, tool-calling workflows, and RAG systems
• Integrate AI capabilities with enterprise products through APIs and MCP
• Optimize prompts, model performance, and AI quality
• Collaborate with Product, Engineering, and Design teams to deliver production-ready AI solutions 

What We Offer

• Work on production AI features with real user impact in a flexible, Agile, multinational team where innovation and collaboration drive everything we do
• Continuous learning and professional growth alongside top talent in the global tech industry
• Hybrid work model, combining remote work with time in our Lviv office
• Daily collaboration with native English speakers, providing a natural opportunity to strengthen your English in a professional environment
• 18 working days of paid vacation, 10 working days of paid sick leave, and 11 paid Ukrainian public holidays

About Our Client

Our client is a leading enterprise data platform company building an open, high-performance data lakehouse for AI and analytical workloads. The platform combines an intelligent SQL query engine, an AI-ready semantic layer, and an open catalog built on Apache Iceberg — enabling Fortune 500 companies across finance, energy, manufacturing, and logistics to unify, query, and govern data at massive scale across cloud and on-premise sources.

About the Role

We are looking for a Senior Software Engineer to build and operate production AI agent and search services on top of a large-scale data platform. This is hands-on work at the intersection of distributed backend engineering and applied AI: multi-agent workflows, tool-execution infrastructure, retrieval and relevance, and integrations with multiple LLM providers — all running as real, customer-facing production services with the reliability expectations that implies.

Responsibilities

• Design and implement scalable multi-agent workflows (including conversation state), tool-execution infrastructure, and data-aware tools working with catalogs, schemas, lineage, SQL, jobs, semantic metadata, data preparation, and visualizations
• Build search and retrieval capabilities with OpenSearch or equivalent — indexing, relevance tuning, hybrid keyword + vector search
• Integrate multiple LLM/model providers with secure configuration and graceful degradation
• Develop APIs and event contracts across REST, streaming/SSE, gRPC, protobuf, and SDKs, including UI integrations
• Operate, monitor, and improve production services — service health, logs, metrics, traces, search-cluster health, latency, and error rates; participate in the team's production-support model
• Investigate incidents, drive root-cause analysis, and ship durable fixes
• Design for permissions, tool approvals, multi-tenancy, and customer-data governance
• Maintain dependencies, apply security fixes, and reduce tech debt; produce designs, tests, runbooks, and documentation; lead technical discussions and review code

Required Qualifications

• B.S. or M.S. in Computer Science, Computer Engineering, or a related field — or equivalent practical experience
• 7+ years of relevant experience, or equivalent demonstrated senior-level impact
• Strong Java software engineering skills
• Strong grasp of concurrency, data structures, API design, testing, maintainability, and backward compatibility
• Solid background in distributed systems, microservices, cloud services, or data-intensive backends
• Hands-on experience with search technologies — OpenSearch, Elasticsearch, or Lucene — including vector search, embeddings, or relevance systems
• Experience building LLM applications, agent/tool workflows, RAG systems, or model-provider integrations
• Strong production instincts: diagnosing failures via logs, metrics, and traces; designing for fault tolerance, retries, cancellation, and recovery
• SQL and familiarity with data platform concepts: catalogs, metadata, schemas, governance, lineage
• Comfort leading ambiguous, cross-service work with clear stakeholder communication and strong written documentation
• Comfortable with AI-assisted development workflows — using modern AI tools productively while critically validating their output
• English Upper-Intermediate or higher (B2+) — daily written and verbal communication with a US-based engineering team
• Availability to work EU business hours shifted 2–3 hours later for daily overlap with US West Coast mornings

Desired Skills

• LangChain4j or similar agent frameworks
• Python for AI services, evaluation harnesses, or sandboxed execution
• React and TypeScript
• gRPC, protobuf, Quarkus, Kubernetes, MongoDB, KV stores, event-driven architectures
• Apache Arrow, Apache Iceberg, OpenLineage, semantic layers, or data-governance systems
• AI quality evaluation: LLM-as-judge, model benchmarking, production AI metrics
• OpenSearch operations: index lifecycle management, relevance tuning, incident response
• Open-source contributions

Details

• Engagement: Long-term contract
• Location: Europe (EU / EEA / UK), remote
• Working hours: EU business hours, shifted 2–3 hours later for daily overlap with the US West Coast team

About the role

This is an on-site position in Abu Dhabi, UAE. We are looking for a hands-on Forward Deployed AI Engineer to build and operate production agentic AI systems within a complex operational business.

You will work directly with stakeholders and a cross-functional engineering squad to understand business challenges, translate them into practical technical requirements, and deliver solutions from discovery and design through implementation, deployment, operation, and continuous improvement. This is a build-first individual-contributor role with end-to-end engineering responsibility for assigned solutions.

What you will do

Understand before you build

• Collaborate directly with stakeholders to translate operational needs into clear technical requirements, constraints, and delivery priorities.
• Contribute across discovery and solution design, then implement, deploy, operate, and continuously improve the resulting systems.
• Challenge assumptions, identify underlying operational drivers, and recognize when AI is not the appropriate solution.

Agentic AI solution development

• Design, build, deploy, and continuously improve enterprise-grade agentic AI applications as the primary engineering approach.
• Develop AI agents capable of multi-step reasoning, tool and API orchestration, context management, exception handling, and human-in-the-loop workflows at enterprise scale.
• Implement Retrieval-Augmented Generation solutions, including data ingestion, chunking, vector representations, vector search, retrieval optimization, grounding, and source traceability.
• Connect AI systems to enterprise platforms through Model Context Protocol (MCP), REST APIs, OpenAPI specifications, webhooks, messaging, and event-driven architectures.
• Create reusable, self-service AI services and interfaces that can support multiple business domains.
• Apply structured LLM engineering practices, including tool calling, schema validation, retries, fallbacks, guardrails, and clear recovery paths.

Quality, reliability and governance

• Take responsibility for the quality of assigned solutions through testing, evaluation, observability, structured logging, version control, and continuous feedback mechanisms.
• Optimize deployed solutions across accuracy, reliability, performance, security, latency, and cost.
• Apply security, privacy, access-control, auditability, responsible-AI, and governance requirements throughout solution design and operation.

Delivery and collaboration

• Work closely with product owners, AI architects, engineers, and business stakeholders across discovery and delivery.
• Implement robust multi-agent systems, agent-to-agent communication patterns, tool-orchestration flows, and evaluation frameworks within the agreed solution architecture.
• Contribute reusable components, documented patterns, implementation guidance, and operational runbooks that other engineers can adopt.
• Participate in design discussions, code reviews, testing, release preparation, production troubleshooting, and post-release improvement.
• Communicate delivery progress, technical risks, dependencies, and trade-offs clearly to technical and non-technical stakeholders.

Required skills and experience

• Demonstrated curiosity and a strong drive to understand complex business and operational challenges before proposing a solution.
• A business-first, human-centered approach that treats AI as a way to augment people rather than replace them.
• Excellent English communication skills and experience working effectively in diverse, international teams.
• Strong experience building production-grade software, including practical delivery with Generative AI, Large Language Models, or applied machine learning and hands-on experience designing and deploying agentic AI solutions.
• Proven ability to deliver AI applications from requirements and design through implementation, deployment, and production support.
• Strong Python programming skills and expertise in at least one additional language: TypeScript/JavaScript, Java, or C#.
• Hands-on experience or strong working knowledge of MCP for connecting AI agents with systems, tools, APIs, and data sources.
• Practical experience with one or more modern agent orchestration frameworks or enterprise AI platforms.
• Strong understanding of asynchronous programming, API development, typed data validation, CI/CD, testing strategies, source control, logging, and error handling.
• Experience with vector databases or search platforms and production RAG patterns.
• Experience integrating enterprise systems through APIs, managed identities, middleware, webhooks, messaging queues, and cloud-native architectures.
• Practical experience deploying containerized solutions in cloud environments with monitoring and observability.
• Strong judgment across quality, latency, reliability, security, governance, and cost trade-offs.

Will be a plus

• Experience in aviation, transportation, logistics, supply chain, cargo operations, customer service, or other complex operational environments.
• Background in classical machine learning, data science, or advanced analytics.
• Full-stack engineering experience across front-end, API, and back-end systems.
• Experience with Voice AI, email automation, CRM integrations, workflow automation, or multilingual AI solutions.
• Experience building evaluation frameworks, golden datasets, simulation-based testing, regression suites, and AI quality-measurement systems.
• Experience designing multi-agent architectures, agent registries, agent-to-agent communication, and tool-orchestration standards.
• Experience working effectively with external AI platforms, startups, or technology providers as part of a broader delivery team.
• Relevant certifications in cloud AI, Generative AI, agentic AI, MLOps, or related disciplines.

Work model and relocation

The role is full-time and onsite in Abu Dhabi, UAE, for an initial one-year assignment with possible extension. The selected candidate will be employed through the designated UAE company. Planned support includes the UAE employment visa, employee medical insurance, an initial flight to the UAE, a return flight at the end of the assignment, an approved broker fee, apartment-search assistance and local arrival support (subject to the final written offer).

About us

DroneOps is a company creating innovative UAV-related products, focused on UAV autonomy and navigation, founded in 2023. We are a team of innovators and inventors who take on the duty to help the armed forces of Ukraine defend our country and democracy by providing reliable advanced systems that simplify their work, improve personnel safety, and enable more cost-effective and precise UAV mission execution.

Overview

We are looking for a Middle / Senior Computer Vision / Deep Learning Engineer to extend our onboard navigation capabilities with modern perception and learning-based methods.

This is a hands-on R&D role: you work from research and prototypes to production on edge hardware, collaborate with software, and flight teams, and help shape how new CV/DL features are built and shipped. The role suits someone who can follow state-of-the-art work, implement what fits our constraints, and care about real-world performance—not only offline benchmarks.

Responsibilities

Relocalization & navigation

• Design and develop satellite, map, and semantic navigation capabilities that improve the overall quality of our navigation
• Build and maintain pipelines for map and reference-data preparation before missions
• Extend the existing visual-inertial navigation stack with relocalization and map-based aiding features
• Develop training pipelines for these tasks (data preparation, training, evaluation, and iteration)
• Create utilities that make map preloading and mission setup convenient for operators and integrators
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Research & implementation

• Track relevant research and industry approaches; prototype and adopt methods where they clearly improve the product
• Reimplement or adapt algorithms when off-the-shelf solutions do not fit our data, hardware, or latency requirements
• Define evaluation metrics and acceptance criteria for new features before field and deployment rollouts
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Edge deployment & production

• Optimize models and inference for target onboard hardware
• Integrate new features into the production codebase with stable APIs, logging, and failure handling
• Take part in architecture decisions, code review, and team practices that keep production quality high as the stack grows
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Required skills & experience

• 3+ years of practical experience in computer vision and deep learning
• Strong Python; ability to write clear, maintainable code for experiments and production paths
• Experience with training and deploying deep learning models (PyTorch)
• Familiarity with model optimization for edge or embedded devices (pruning, quantization, ONNX/TensorRT-class tooling, or equivalent)
• Comfort working with geospatial or map-related data and preprocessing pipelines
• Practical production mindset: reproducible experiments, versioning, and validation on real data
• English B2+ for documentation and technical discussion; Ukrainian for day-to-day team communication
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Nice to have

• Experience with deep learning keypoint detection and matching approaches
• Comfortable with geometric computer vision (camera models, epipolar geometry, robust estimation)
• Multi-sensor fusion / SLAM / EKF background
• UAV, robotics, or aerospace field experience
• Experience with satellite or aerial imagery, semantic segmentation, or visual place recognition
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What we offer

• Competitive salary
• Reservation from mobilization
• Impact on improving our country's defense capabilities
• 21 days of vacation + public holidays, sick leaves