Jobs ML / AI

Cloudfresh ⛅️ is a Global Google Cloud Premier Partner, Zendesk Premier Partner, Asana Solutions Partner, GitLab Select Partner, Hubspot Platinum Partner, Okta Activate Partner, and Microsoft Partner.

Since 2017, we’ve been specializing in the implementation, migration, integration, audit, administration, support, and training for top-tier cloud solutions. Our products focus on cutting-edge cloud computing, advanced location and mapping, seamless collaboration from anywhere, unparalleled customer service, and innovative DevSecOps.

We're looking for an AI Architect to become our lead technical expert for client AI solutions and to help stand up our AI Competence Centre and internal AI Lab.

This is a client-facing technical role first, with a build-and-lead dimension. Expect roughly 60% solution architecture and pre-sales engineering for enterprise clients, and 40% establishing the AI Lab and mentoring engineers. You'll technically lead and raise the bar for the team - this is a technical leadership role, not a people-management line.
Reports to: Head of AI.

Requirements

• Experience & seniority. 5+ years in software, data, or ML engineering, including 3+ years delivering ML/AI in production and 2+ years in a client-facing architect or technical lead capacity.
• Cloud & AI infrastructure. Production-level experience on Google Cloud Platform, especially the Vertex AI suite, plus integrating third-party model providers such as Anthropic.
• GenAI engineering. Strong hands-on knowledge of RAG, agentic workflows, orchestration frameworks (LangChain, LlamaIndex), vector databases, and prompt/context engineering.
• Production & MLOps. Hands-on with the ML lifecycle, CI/CD for models, automated deployment, and cloud cost management - including right-sizing models (lighter vs. heavier) to control spend.
• Evaluation, guardrails & observability. Practical experience building LLM evaluations, guardrails, and monitoring for accuracy, safety, latency, and cost in production.
• AI governance & security. Familiarity with data governance, model risk, and EU regulation (EU AI Act, GDPR) as it applies to enterprise AI — we're primarily EU-based.
• Pre-sales & client experience. Proven experience presenting to enterprise clients, scoping technical projects, and translating complex AI concepts into clear business value.
• Technical leadership. Experience guiding engineers, reviewing architecture and code, and raising team capability.
• Languages. Native Ukrainian — required, as you'll run Ukrainian-language pre-sales — and strong English (B2+/C1 minimum).

• Mindset & agility. An intrapreneurial drive to build an AI Lab from scratch inside an established business, plus the agility to move smoothly between client pre-sales and deep technical architecture.

   

Responsibilities

• Solution architecture. Design and own end-to-end AI systems for strategic enterprise clients - reference architectures, data and retrieval pipelines, agentic layers, and integration with existing enterprise systems - with a clear path from prototype to scalable, secure, observable production.
• Pre-sales & consulting. Partner with sales to qualify and win AI opportunities: run technical discovery, scope solutions, size effort and cost, and translate AI into business value, ROI, and risk for C-level stakeholders.
• Technical leadership & mentorship. Set architecture and engineering standards, run design and code reviews, and level up engineers across the AI practice.
• AI Lab & R&D. Stand up and run the internal AI Lab - rapid client prototypes and cost-effective internal AI tooling - with a clear bar for what graduates into production.
• Partner collaboration. Work with our core AI partners (Google Cloud / Vertex AI, Anthropic) to build joint solutions, access early capabilities, and shape our technical roadmap.
• Governance, security & cost. Build guardrails, evaluation, and observability into every solution; keep architectures compliant (EU AI Act, GDPR) and cost-aware through right-sized model selection.

Would be a plus

• Google Cloud Professional Machine Learning Engineer and/or Professional Cloud Architect certification.
• Hands-on enablement or certification with Anthropic and Vertex AI generative-AI stacks.
• Direct experience mapping solutions to the EU AI Act risk framework.
• Fine-tuning, distillation, or model-optimization experience.
• Production experience with voice/multimodal AI (e.g., ElevenLabs) or AI-assisted engineering tooling (e.g., Cursor).
• Contributions to the open-source GenAI ecosystem.

Work conditions

• Flexible Work Format: Work remotely, allowing you to balance your professional and personal life efficiently.
• Training with Leading Cloud Products: Access in-depth training on cutting-edge cloud and AI solutions, enhancing your expertise and equipping you with the tools to succeed in an ever-evolving industry.
• International Collaboration: Work alongside A-players and seasoned professionals in the cloud industry.
• Global Exposure: Expand your expertise by engaging with international markets across the EMEA and CEE regions.
• Vibrant Team Environment: Be part of an innovative, dynamic team that fosters both personal and professional growth, creating opportunities for you to advance in your career.
  
  When applying to this position, you consent to the processing of your personal data by CLOUDFRESH for the purposes necessary to conduct the recruitment process, in accordance with Regulation (EU) 2016/679 of the European Parliament and of the Council of April 27, 2016 (GDPR).
  Additionally, you agree that CLOUDFRESH may process your personal data for future recruitment processes. You can withdraw this consent at any time.

Backend Software Engineer (Python, AI)
 

Requirements:
- 6+ years of experience in backend design and development of production-grade applications.
- Strong experience with Python
- Solid experience with databases, preferably SQL
- Experience working with large-scale systems
- Experience with AI orchestration frameworks such as LangChain or LlamaIndex, or experience integrating third-party AI APIs such as OpenAI or Anthropic.
- Knowledge of networking infrastructure.
- Cybersecurity experience - a strong advantage.
- Ability to learn quickly and adapt to new technologies.
- Strong teamwork and collaboration skills.
 

Responsibilities:
- Take full ownership of features, from product design through deployment, including end-to-end feature architecture.
- Plan, design, and develop systems with complex performance and scalability requirements.
- Design, maintain, and contribute to the company’s code infrastructure.
- Design, build, and maintain robust, scalable server-side architecture.
- Integrate with Large Language Models (LLMs) and vector

About ByChat FinOps

ByChat FinOps is a production-ready B2B AI platform that helps organizations understand, analyze, and optimize cloud infrastructure costs across AWS.

Our platform combines cloud billing data with Generative AI, enabling users to ask natural language questions such as:

• Why did our cloud costs increase this month?
• Which services generate the highest expenses?
• Will we exceed our budget next quarter?
• Where can we reduce infrastructure costs?
   

Behind the scenes, intelligent LLM Agents work with cloud APIs, read-only SQL queries, billing datasets, forecasting models, anomaly detection algorithms, and FinOps analytics to deliver accurate, explainable business insights.

ByChat FinOps is an actively growing production product where AI reliability, security, scalability, and measurable business value are our highest priorities.
 

About the Role

We are looking for a Senior / Lead ML Consultant to support our engineering team on a part-time basis and provide expert guidance on the architecture, development, evaluation, and optimization of our AI/ML capabilities.

This is primarily an advisory and technical leadership role rather than a full-time hands-on engineering position.

You will work closely with our AI/ML engineers and technical team, review existing approaches and processes, identify potential risks and inefficiencies, and provide practical recommendations for improving the quality, reliability, and efficiency of our AI systems.

We expect you to act as a senior technical advisor and sparring partner for the team, helping us validate technical decisions and ensure that our ML/LLM practices meet production-grade standards.
 

What You'll Do

Your responsibilities will include:

• Review the architecture and implementation of our AI/ML and LLM-based solutions.
• Provide regular technical feedback to AI/ML engineers and help validate key engineering decisions.
• Review existing ML/LLM development processes and recommend improvements.
• Evaluate the effectiveness, reliability, and scalability of current AI workflows.
• Advise the team on the design of LLM Agents, sub-agents, tool calling, structured outputs, and agentic workflows.
• Review approaches to prompt engineering, context management, guardrails, validation, retries, and hallucination mitigation.
• Assess and improve LLM evaluation methodologies, automated testing, golden datasets, and quality metrics.
• Advise on AI observability, tracing, monitoring, and production quality control.
• Review Text-to-SQL approaches and help ensure safe and reliable interaction with financial datasets.
• Provide guidance on anomaly detection, forecasting, and other ML components used within the platform.
• Identify performance bottlenecks and opportunities to optimize LLM latency, token usage, infrastructure usage, and operational cost.
• Help the team evaluate new AI/ML technologies, frameworks, models, and architectural approaches before introducing them into production.
• Participate in technical discussions and architecture reviews for complex AI-related features.
• Mentor engineers and help strengthen the team's ML/LLM engineering practices.
• Help establish practical engineering standards and best practices for building production-grade AI systems.
   

What We Expect

Must Have

• Strong senior-level commercial experience in Machine Learning / AI Engineering, ideally including technical leadership or consulting responsibilities.
• Proven experience designing and reviewing production AI/ML systems.
• Strong practical experience with modern LLM applications and Agentic AI systems.
• Deep understanding of:
  • LLM Agents and agentic workflows
  • Prompt Engineering
  • Function / Tool Calling
  • Structured Outputs
  • Context management
  • Hallucination mitigation
  • Guardrails and validation
  • Retry and fallback strategies
• Strong understanding of ML/LLM evaluation methodologies and how to measure AI system quality in production.
• Experience with AI observability, tracing, testing, and monitoring.
• Strong Python and SQL knowledge with the ability to review implementation and architecture decisions.
• Understanding of statistics, anomaly detection, forecasting, and data-driven system evaluation.
• Experience identifying technical risks, architectural weaknesses, and performance bottlenecks.
• Ability to translate complex technical findings into clear, practical recommendations for an engineering team.
• Strong communication and mentoring skills.
• English sufficient for technical discussions, documentation, and regular communication with the team.
   

Nice to Have

• Previous experience as a Lead ML Engineer, ML Architect, AI Architect, Staff/Principal ML Engineer, or ML Consultant.
• Experience with LangChain, LangGraph, or other Agent frameworks.
• Experience with AWS Bedrock, Claude, or other managed LLM platforms.
• Experience with FinOps, cloud billing, or cloud cost optimization.
• Knowledge of:
  • AWS CUR
  • AWS Cost Explorer
• Experience with Langfuse, LangSmith, RAGAS, or similar AI observability and evaluation platforms.
• Experience designing evaluation pipelines and golden datasets for LLM applications.
• Experience with forecasting and time-series analysis.
• Experience processing large financial or billing datasets.
• Understanding of multi-tenant architectures and secure AI tool execution.
• Experience optimizing LLM latency, token usage, and operational costs.
   

Technology Stack

• Python 3.12
• FastAPI
• LangChain
• LangGraph
• AWS Bedrock
• PostgreSQL
• SQL
• Langfuse
• RAGAS
• Docker
• Next.js / TypeScript
   

Engagement Format

• Part-time consulting engagement
• Flexible involvement based on project and team needs
• Regular technical reviews and consultations with the AI/ML team
• Architecture and solution reviews for key AI/ML initiatives
• Focus on technical guidance, quality assurance, process improvement, and mentoring rather than day-to-day feature implementation
   

Why Join Us?

• Influence the technical direction of a real production AI product without committing to a full-time role.
• Work on challenging problems at the intersection of Generative AI, Agentic AI, Cloud, and FinOps.
• Help shape the architecture and engineering practices behind production-grade AI systems.
• Work with a team that values measurable AI quality, reliability, security, and business impact.
• Apply your senior-level expertise where it has the highest impact: technical decisions, architecture, evaluation, optimization, and team development.
• Stay close to modern AI technologies while working in a flexible consulting format.

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

🔹Who we are!

At Levi9, we are passionate about what we do. We love our work and together in a team, we are smarter and stronger. We are looking for skilled team players who make change happen. Are you one of these players?

🔹About the project

You will join a dynamic, cross-functional AI team building AI prototypes, from classic ML to advanced LLM applications such as Text-to-SQL and complex RAG systems. Our goal is to engage our customers with advanced AI solutions.

🔹Responsibilities

• Design and deploy predictive ML models (e.g., decision trees, random forests, gradient boosting) for analytics and feature engineering.
• Develop recommendation systems using collaborative and content-based filtering techniques.
• Build and enhance RAG systems, including embedding pipelines, managing vector databases, and integrating LLMs.
• Implement text-to-SQL capabilities, allowing users to query relational databases naturally using LangChain or similar technologies.
• Work alongside data engineers to ensure robust data pipelines and high-quality datasets for training and inference.
• Collaborate with Product Owners and UX Designers to align AI features with user needs and business goals.
• Continuously research, test, and apply cutting-edge algorithms and technologies to boost model performance and scalability.
• Monitor and improve production models, ensuring reliability, performance, and compliance with ethical standards.
   

🔹Requirements

• Experience: 4+ years in AI/ML, specifically building and deploying production-level ML models.
• Classic ML: Solid skills with decision trees, random forests, and gradient boosting methods (scikit-learn, XGBoost).
• Recommender Systems: Proven experience in collaborative and content-based recommendation algorithms.
• RAG & LLM Development: Hands-on expertise with retrieval-augmented generation systems, vector databases (Pinecone, Weaviate), and frameworks like LangChain or LlamaIndex.
• Text-to-SQL: Experience developing natural-language-to-SQL solutions using frameworks like LangChain.
• Programming & Data: Advanced Python proficiency, strong SQL skills, and familiarity with Pandas and NumPy.
• Cloud & MLOps: Knowledge of deploying models on AWS, Azure, or GCP, and familiarity with CI/CD and MLOps tools (MLflow, Kubeflow).
• Communication: Comfortable in Agile teams with excellent English communication skills.

🔹Will be a plus

• Experience with Docker and Kubernetes.
• Familiarity with advanced embedding techniques and optimizing similarity searches.
• Background in deep learning frameworks such as TensorFlow or PyTorch.
• Knowledge of ethical AI practices and data privacy standards.

🔹 Our customer's stack
Core — Python 3.13, LangGraph and LangChain for agent orchestration, AWS Bedrock for inference, retrieval, and runtime (AgentCore, Knowledge Bases, Guardrails), Pydantic for schema enforcement, CloudFormation for infrastructure.
Quality — pytest across unit, integration, and e2e tiers with a coverage gate, ruff, mypy and pyright, promptfoo for prompt and output evaluation. We hold agent code to the same bar as any other production system.

🔹9 reasons to join us:

1. Today we're working with the technology of tomorrow.
2. We don't wait for a change. We are the change.
3. We're experts in creating experts (Levi9 academy, Lead9 program for leaders).
4. No micromanagement. We are free birds with a clear understanding of what high performance is!
5. Learning in Levi9 never stops (unlimited Udemy for business, meetups, English courses, Professional trainings).
6. Here you can train your body and mind.
7. We've gathered the best locations - comfortable, cozy and pet-friendly offices in Kyiv (5 minutes from Olimpiyska subway station) and Lviv (5 minutes from the Opera Theatre) with regular offline internal events
8. We have master's degree in work-life balance.
9. We are actively supporting Ukraine with constant donations and volunteering
    

🔹Simple steps to get this job

Click the APPLY NOW button and leave your contacts!

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:

This is a hyper-scale fintech platform trusted by over 40 million users worldwide, offering access to multi-asset trading - including stocks, indices, currencies, and digital assets.

The product operates as a regulated, data-intensive financial ecosystem, processing massive volumes of transactions and real-time customer interactions daily. It’s well-funded, profitable, and known for pushing innovation in AI, automation, and data governance across its operations. Advertising presence is strong (especially in the UK), but behind the scenes is a serious engineering culture solving hard, real-world problems at scale.

About the Role:

We are looking for an Applied AI Engineer (Squad Lead) to join a fast-paced, AI-first environment where AI is already a core part of how the company operates. This is not a role where you’ll be adding an AI feature to an existing product or experimenting with isolated prototypes. You’ll take real business challenges, work directly with stakeholders to understand what needs to change, and turn those problems into production-grade AI agents and applications — end to end, from idea and POC to deployment and continuous improvement.

This is a deeply hands-on role with significant autonomy and ownership. You’ll work with modern GenAI and agentic technologies, use AI-native development workflows daily, and see the impact of your solutions quickly. As the squad grows, you’ll also guide other engineers while remaining hands-on.

Key Responsibilities:

• Design, build, and deploy AI-powered agents and applications from concept through production.
• Develop and maintain AI pipelines for data ingestion, embeddings, retrieval, and LLM orchestration.
• Write high-quality backend and frontend code to embed AI into user-facing tools and internal platforms.
• Build APIs and integrations with internal systems (CRM, databases, third-party services) for seamless automation and data flow.
• Work with structured, unstructured, and vectorized data to support intelligent workflows and decision-making.
• Continuously monitor, evaluate, and iterate to improve system performance, reliability, and cost efficiency.
• Design and implement scalable, secure, observable, cloud-based solutions.
• Own production systems, including debugging, enhancements, and ongoing optimization.
• Collaborate closely with product and business stakeholders to translate requirements into high-impact solutions.

Required Competence and Skills:

• 5+ years of software engineering experience (backend or full-stack).
• Proven daily use of AI-native development workflows (e.g., Cursor, Claude Code) for production systems.
• Hands-on experience building production AI agents, including RAG, multi-agent orchestration, tool-calling, structured outputs/validation, memory, and workflow management.
• Experience with agent orchestration and evaluation frameworks (LangChain, LangGraph, LangSmith, Semantic Kernel or equivalent).
• Track record of deploying LLM-powered systems in production.
• Strong backend and modern frontend development skills for complex workflows.
• Experience with cloud services (Azure, AWS, or GCP) and designing scalable architectures.
• Familiarity with vector databases and embedding pipelines.
• Deep understanding of system design, scalability, observability, and security best practices.
• Experience leading small development teams or owning a technical domain.
• Excellent communication, stakeholder management, and problem-solving skills.
• Fluent written and verbal English.

Nice to Have:

• Experience building AI systems in regulated or compliance-driven environments.
• Background working with internal teams and platforms (e.g., customer service, retention, operations, compliance).
• Strong understanding of business process automation and operational intelligence.
• Familiarity with event-driven architectures and distributed systems.
• Experience implementing AI evaluation frameworks and automated testing for LLM systems.

We are currently seeking a skilled and driven Senior AI/ML Engineer to join our R&D team.

We believe that you have:

• In-depth knowledge of Machine Learning (ML) and Deep Learning (DL) principles
• A minimum of 3 years of experience working as a Software/ML Engineer
• Strong proficiency in Python programming and ML related libraries and engines
• Experience with AI Agents
• Proven experience in prompt engineering, Large Language Models (LLM)
• LLM Fine-tuning: Experience in fine-tuning pre-trained language models for specific tasks or domains
• LLM Frameworks and Tools: Langchain / LlamaIndex or other + familiarity with other relevant frameworks such as Transformers, GPT-Index, or FAISS
• Experience with one or more machine learning libraries such as TensorFlow, Keras, PyTorch
• Ability to extract meaningful business insights from data and identify the stories behind the patterns
• Willingness to work in an R&D team with shifting priorities and actively engage in PoC initiatives.

• Intermediate or higher level of English proficiency

   

Cool to have:

• Experience with Computer Vision
• Expirience with LLMOps
• DevOps & MLOps: CI/CD pipelines, Docker, Kubernetes
• Experience with SQL, NoSQL and Vector databases

• Experience with NLP, NLU, Semantic Search

   

Responsibilities:

• Collaborate closely with the web development team to design, develop, and deploy machine learning models
• Develop new machine learning models or enhance existing ones to meet project requirements

• Monitor and maintain machine learning models in production, ensuring their optimal performance and stability

   

We offer:

• Flexible schedule
• Horizontal management and communication directly with project stakeholders
• 20 days of paid vacation
• Paid sick-leaves
• Annual activities budget — we endorse your wish to self-improvement
• Remote work

SupportYourApp is an international Intelligent Support-as-a-Service company that has been providing business process outsourcing services to IT companies around the globe for the past 15 years. We have 1500+ people in our international community.

We operate globally, supporting clients in 60 languages and partnering with industry leaders like MasterCard, Calm, and MacPaw. With international hubs and coworking spaces around the world, we develop innovative products like Quidget and continuously work to improve the customer experience.

About the role:

We are looking for an AI Solutions Specialist to join our team and lead the design and implementation of AI-powered solutions for customer support and business operations.

In this role, you will translate business and operational requirements into scalable technical solutions, design AI architectures, evaluate technologies and integrations, and guide solutions from discovery through implementation.

You will work closely with clients, internal teams, and technical stakeholders to identify the right AI approach for each use case and ensure that solutions are reliable, scalable, and aligned with business goals.

What you will do:

• Design end-to-end AI solutions based on client business and technical requirements;
• Define solution architecture, integrations, data flows, and implementation approach;
• Design and implement AI-powered solutions, including conversational AI, chatbots, agent assist, and automation;
• Work with LLMs, RAG, prompt engineering, AI agents, and knowledge retrieval systems;
• Lead technical discovery and solution design sessions with clients and internal teams;
• Conduct demos of proposed AI solutions and explain their functionality, capabilities, and business value;
• Troubleshoot technical issues and drive solutions through to resolution.

What you need to succeed in this role:

• Fluency in English (C1+ / Advanced+);
• Practical experience taking an AI support solution from implementation/configuration to actual use by customers or support teams;
• Experience implementing AI-powered chatbots and voicebots specifically for customer support or customer service operations;
• Hands-on experience with AI and automation platforms (for example, Zendesk AI Agents, n8n, Voiceflow, Botpress, Cognigy, or similar tools);
• Understanding of LLMs, Generative AI, RAG, prompt engineering, and AI agents;
• Basic understanding of APIs, integrations, databases, and system architecture;
• Ability to translate business requirements into scalable technical solutions and communicate technical concepts to both technical and non-technical stakeholders.

Will be an advantage:

• Hands-on experience with helpdesk platforms (for example, Zendesk, Freshdesk, and Intercom), including their automation and AI features;
• Experience with AI evaluation, monitoring, and guardrails;
• Experience working directly with clients during technical discovery and solution design;
• Experience leading implementation projects.

Benefits and Perks:

• Providing services during business hours;
• Opportunity to cooperate fully remotely;
• Inclusive international environment;
• Compensation in USD;
• Rewards for referring friends;
• Balance between project workload and personal time, but also – internal health policy;
• Responsive leadership interested in your growth and long-lasting cooperation;
• Greenhouse conditions for self-development;
• A culture built on trust, with no time-tracking requirements.

*The items listed in this section may vary depending on the terms of your engagement. Certain benefits and conditions typically apply to employees; independent contractors may not be eligible for all of these. The specific terms, including compensation, benefits, and work conditions, will be clearly defined in your agreement if selected.

Are you passionate about connecting systems and driving intelligent automation? Do you thrive in fast-paced environments where you can analyze workflows, implement AI solutions, and collaborate with teams to deliver scalable, high-impact results?

Grab the chance to join us and send your CV in English, pointing out your outstanding skills!

Know someone perfect for the role? Refer them and get rewarded! 

We adhere to the principles of equal treatment of candidates and prohibit discrimination on any grounds protected by law.

Your personal data will be processed as described in the SupportYourApp Candidate Privacy Notice.

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.

Brief introduction
You will build production RAG and LLM systems that read real documents and run inside enterprise ERP and finance stacks.

This is a solo, end-to-end role. You join client calls, design the architecture, then build the important parts yourself. Our core stack is Python, Django, Angular and RAG. Ukraine/EU hours.

About us

Deploy Staff automates the manual work large enterprises run on: finance, operations, customer service, reporting. We build complex systems for clients in the US and UAE (currently primarily UAE), centered on production RAG and LLM workflows that read real documents and integrate with real ERP and finance systems.

Despite the name, we don't place engineers into other people's teams. We are not an outstaff company. We own the solutions we build end to end, and so will you.

The role

Solo and end to end. You are the engineer on your projects: there is no development team, and the technical work is yours from discovery through production support.

You sit in on client calls with the project manager, understand the business problem, design the architecture, then open the codebase and build it yourself. The PM runs the relationship and the commercial side. You own the system.

Solo does not mean isolated. You have direct access to the people making decisions, and we talk architecture through with you before you commit to it. After that the code is yours to write and merge. Part of the job is judgement about which calls are yours and which should come back to us, and we would rather be asked than surprised.

If you have spent recent years distributing work and reviewing it, this will feel like a step backwards. If you have spent them wishing there were fewer people between you and the problem, it will not.

What we expect

Our core stack is Python, Django, Angular and RAG/LLM-based workflows. That is what we need you to already be good at.

Core

• Production LLM work: RAG (retrieval design, chunking, evaluation), document processing, structured extraction or agentic workflows. Shipped and operated by you, through the parts that only show up after real users arrive
• Strong Python with Django or DRF, and PostgreSQL data models you can design and debug in production
• Angular and TypeScript. You own the frontend of what you build, so you need to be able to ship a feature through it without waiting for anyone
• Advanced English (C1). You will question senior stakeholders directly and explain a decision a second way when the first one does not land

Also part of the work

You will hit all of this. We do not expect equal depth in every line, and we do expect you to pick up what you are missing.

• Celery, Redis, queues and asynchronous processing
• Enterprise integration: ERP, finance, CRM systems and their APIs
• Cloud infrastructure, deployment, observability and security. AWS, GCP, Kubernetes, Docker
• Reading an existing system before changing it, and keeping what already works

What matters more than the CV

What you personally built, what you personally decided, and what happened when it broke. If your strongest examples are systems your team implemented while you supervised, this is not the right fit.

How we work

Remote, with working hours aligned to the Ukraine time zone.
Small team, direct access to decision makers, real operational problems. You get problems to solve rather than specs to implement.

Interview

1. Introductory interview.

2. Technical interview with us.

3. Test task.

4. Offer.
Interviews are recorded and shared only within the hiring team, so decisions are made on what you actually said rather than someone's notes.

Repeating once again - our core stack is Python, Django, Angular and RAG! We cannot compromise on any of these. If one of those isn't present or barely used - this is an immediate mismatch!

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’re looking for a brilliant Deep Learning & Computer Vision engineer to join our Algorithms group.
 

What will you do?

• Be a researcher of the core deep learning algorithms and communicate with other researchers.
• Design and implement advanced algorithms to solve complex problems.
• Developing the next generation algorithms including different CNN architectures, CV algorithms and algorithms that utilize Physics in complex environment.

Requirements

• At least 5 years’ experience as a researcher and development of deployed models.
• Strong understanding in deep-learning algorithms and computer vision.
• M.Sc. in computer science, or very experienced BSc Degree Guide 2025 — Online BSc Courses & Programs . or Engineering, or a related technical field.
• Experience in Python & PyTorch or other machine learning frameworks and mathematical modelling.
• Good communication skills, self-motivated, proactive, flexible and passionate about learning.
• Focused on end-to-end delivery of solutions for real world scenario in challenging timeframe.

Development and enhancement of automation solutions using the uiAgent platform
Automation of heat, electricity, and gas bill processing
Implementation of validation, testing, and processing logic
Further development and stabilization of existing bots and workflows
Adaptation of automations to changes in ERP/Business Central systems
Integration of existing partial automations into end-to-end processes
Conducting tests, error analyses, and regression tests
Support during go-live, hypercare, and business acceptance testing
Analysis, documentation, and optimization of existing processes
Coordination with product owners, business units, business IT, and technology partners
Requirements
Experience in RPA/software automation and the development of automated business processes
Experience with uiAgent or comparable automation platforms
Knowledge of ERP systems, ideally Microsoft Dynamics 365 Business Central
Experience Experience with invoicing and procure-to-pay processes
Ideally, knowledge of the energy industry
Experience with UI automation, testing, and error analysis
Structured and independent work style
Fluent in German and English