Machine Learning Engineer – General ML & Generative AI (B2B)

🏢 Summary: Machine Learning Engineer role focused on designing, deploying, and operating enterprise-grade classical ML and Generative AI solutions in hybrid cloud environments. The position involves building end-to-end ML pipelines, integrating LLM-based systems, and ensuring production stability and scalability. Candidates work closely with ML and data teams while concentrating on technical implementation and operational excellence. 🗂️ Requirements: Degree in Computer Science, Data Science, Mathematics or related field, Experience delivering Generative AI solutions, Understanding of LLM architectures and limitations, Strong Python engineering skills, Knowledge of clean code and software engineering best practices, Experience with Git-based version control, Experience working with CI/CD pipelines, Experience with ML and GenAI platforms, Experience with cloud environments, Fluent English, Fluent Polish, Availability for hybrid work with 1–2 office visits per week 📃 Skills: Python, Git, CI/CD, Databricks, AWS, Azure, GCP, LLM, GenAI, MachineLearning 🏢 Description: Responsibilities As a Machine Learning Engineer with a focus on classical ML as well as Generative AI, you are responsible for the technical design, implementation, and operation of enterprise-grade ML & GenAI solutions. You work in a tandem setup with an internal colleague who manages stakeholder communication and overall delivery, allowing you to concentrate on the technical realization, integration, and operational stability of ML & GenAI use cases. Design, train and optimize classical machine learning and Generative AI models for enterprise-grade use cases Build and maintain end-to-end ML and GenAI pipelines including data preparation, feature engineering, training, validation, deployment and monitoring Ensure robustness, performance and reproducibility of ML and GenAI solutions running in production Integrate LLM-based solutions using APIs and GenAI frameworks into existing system landscapes Collaborate closely with internal ML engineers and data teams on technical design, implementation and operational topics Qualifications Successfully completed university degree in Computer Science, Data Science, Mathematics or a related field Practical experience delivering Generative AI solutions and a solid understanding of LLM architectures and limitations Strong Python engineering skills, including clean code practices and software engineering best standards Hands-on experience with Git-based code versioning and working with CI/CD pipelines as a user Experience with productive ML and GenAI platforms and cloud-based environments (e.g. Databricks, AWS, Azure or GCP) Fluent communication skills in English and Polish and availability to work in a hybrid mode with 1–2 office visits per week. About OBI Smart Technologies WHO ARE WE: We are a joint venture between OBI and Reply Group, responsible for co-designing, building and operating mission-critical digital platforms for commerce, customer service, and omnichannel retail. OUR MISSION: " We unite technology leadership with deep retail vision to implement standardized processes and scalable digital products that drive efficient support for one of Europe’s largest DIY retailers. Leveraging proven best practices, we advance the internationalization of products and the digital mindset of our partners, delivering consistent and business-critical solutions to support the targets of our customer. "

🏢 Summary: Machine Learning Engineer role focused on designing, deploying, and operating enterprise-grade classical ML and Generative AI solutions. The position involves building end-to-end ML pipelines, integrating LLM-based applications, and ensuring production stability in cloud-based environments. The role includes hybrid work, ongoing training opportunities, and a flexible benefits platform. 🗂️ Requirements: Degree in Computer Science, Data Science, Mathematics or related field, Experience delivering Generative AI solutions, Knowledge of LLM architectures and limitations, Strong Python engineering skills, Experience with Git-based version control, Experience working with CI/CD pipelines, Experience with ML and GenAI platforms, Experience with cloud environments, Fluent English, Fluent Polish, Availability for hybrid work with 1–2 office visits per week 📃 Skills: Python, Git, CI/CD, Databricks, AWS, Azure, GCP, LLM, GenAI, MachineLearning 🏢 Description: Responsibilities As a Machine Learning Engineer with a focus on classical ML as well as Generative AI, you are responsible for the technical design, implementation, and operation of enterprise-grade ML & GenAI solutions. You work in a tandem setup with an internal colleague who manages stakeholder communication and overall delivery, allowing you to concentrate on the technical realization, integration, and operational stability of ML & GenAI use cases. Design, train and optimize classical machine learning and Generative AI models for enterprise-grade use cases Build and maintain end-to-end ML and GenAI pipelines including data preparation, feature engineering, training, validation, deployment and monitoring Ensure robustness, performance and reproducibility of ML and GenAI solutions running in production Integrate LLM-based solutions using APIs and GenAI frameworks into existing system landscapes Collaborate closely with internal ML engineers and data teams on technical design, implementation and operational topics Benefits Motivizer Benefits Platform to choose and manage all your benefits in one place. You receive a budget (550 PLN monthly). You can choose medical care package, meal tickets, sports cards (we have Multisport and on preferential terms, we have membership cards to one of the most popular Gyms), cinema tickets, shop vouchers, discounts and many more. Language Courses – you'll have access to a multi-language learning platform enabling you to practice your language skills and learn new ones! Regular and systematic further training opportunities - both internally and from external providers. We support your ongoing learning and development. Cooperation within an internal community is our everyday reality. We have networking events, coding challenges, and company parties for different occasions. Qualifications Successfully completed university degree in Computer Science, Data Science, Mathematics or a related field Practical experience delivering Generative AI solutions and a solid understanding of LLM architectures and limitations Strong Python engineering skills, including clean code practices and software engineering best standards Hands-on experience with Git-based code versioning and working with CI/CD pipelines as a user Experience with productive ML and GenAI platforms and cloud-based environments (e.g. Databricks, AWS, Azure or GCP) Fluent communication skills in English and Polish and availability to work in a hybrid mode with 1–2 office visits per week. About OBI Smart Technologies WHO ARE WE: We are a joint venture between OBI and Reply Group, responsible for co-designing, building and operating mission-critical digital platforms for commerce, customer service, and omnichannel retail. OUR MISSION: " We unite technology leadership with deep retail vision to implement standardized processes and scalable digital products that drive efficient support for one of Europe’s largest DIY retailers. Leveraging proven best practices, we advance the internationalization of products and the digital mindset of our partners, delivering consistent and business-critical solutions to support the targets of our customer. "

🏢 Summary: The offer is for a Machine Learning Engineer responsible for designing, implementing, and operating enterprise-grade Machine Learning and Generative AI solutions. The role focuses on building end-to-end ML and GenAI pipelines, integrating LLM-based solutions, and ensuring production robustness and performance. You will concentrate on technical delivery and system integration within cloud-based environments. 🗂️ Requirements: University degree in Computer Science, Data Science, Mathematics or related field, Practical experience delivering Generative AI solutions, Strong understanding of LLM architectures and limitations, Strong Python engineering skills, Experience with Git-based version control, Experience working with CI/CD pipelines, Hands-on experience with ML and GenAI platforms, Experience with cloud environments (AWS, Azure, GCP or Databricks), Experience building and operating production-grade ML systems 📃 Skills: Python, MachineLearning, GenerativeAI, LLM, Git, CICD, Databricks, AWS, Azure, GCP, APIs, MLOps 🏢 Description: Responsibilities As a Machine Learning Engineer with a focus on classical ML as well as Generative AI, you are responsible for the technical design, implementation, and operation of enterprise-grade ML & GenAI solutions. You work in a tandem setup with an internal colleague who manages stakeholder communication and overall delivery, allowing you to concentrate on the technical realization, integration, and operational stability of ML & GenAI use cases. Design, train and optimize classical machine learning and Generative AI models for enterprise-grade use cases Build and maintain end-to-end ML and GenAI pipelines including data preparation, feature engineering, training, validation, deployment and monitoring Ensure robustness, performance and reproducibility of ML and GenAI solutions running in production Integrate LLM-based solutions using APIs and GenAI frameworks into existing system landscapes Collaborate closely with internal ML engineers and data teams on technical design, implementation and operational topics Benefits Motivizer Benefits Platform to choose and manage all your benefits in one place. You receive a budget (550 PLN monthly). You can choose medical care package, meal tickets, sports cards (we have Multisport and on preferential terms, we have membership cards to one of the most popular Gyms), cinema tickets, shop vouchers, discounts and many more. Language Courses – you'll have access to a multi-language learning platform enabling you to practice your language skills and learn new ones! Regular and systematic further training opportunities - both internally and from external providers. We support your ongoing learning and development. Cooperation within an internal community is our everyday reality. We have networking events, coding challenges, and company parties for different occasions. Qualifications Successfully completed university degree in Computer Science, Data Science, Mathematics or a related field Practical experience delivering Generative AI solutions and a solid understanding of LLM architectures and limitations Strong Python engineering skills, including clean code practices and software engineering best standards Hands-on experience with Git-based code versioning and working with CI/CD pipelines as a user Experience with productive ML and GenAI platforms and cloud-based environments (e.g. Databricks, AWS, Azure or GCP) Fluent communication skills in English and Polish and availability to work in a hybrid mode with 1–2 office visits per week. About OBI Smart Technologies WHO ARE WE: We are a joint venture between OBI and Reply Group, responsible for co-designing, building and operating mission-critical digital platforms for commerce, customer service, and omnichannel retail. OUR MISSION: " We unite technology leadership with deep retail vision to implement standardized processes and scalable digital products that drive efficient support for one of Europe’s largest DIY retailers. Leveraging proven best practices, we advance the internationalization of products and the digital mindset of our partners, delivering consistent and business-critical solutions to support the targets of our customer. "

🏢 Summary: The role focuses on designing, building, and operating production-grade machine learning solutions using classical ML and deep learning models. You will develop end-to-end ML pipelines, ensure robustness and reproducibility in production, and collaborate on technical solution design. The position emphasizes strong Python engineering and experience with cloud-based ML platforms. 🗂️ Requirements: Degree in ComputerScience, DataScience, Mathematics or related field, Experience building production-grade machine learning pipelines, Strong Python engineering skills, Experience with Git-based version control, Experience working with CI and CD pipelines, Experience with cloud-based ML platforms, Ability to design, train and optimize ML and deep learning models, Experience ensuring robustness and reproducibility in production environments 📃 Skills: Python, MachineLearning, DeepLearning, Pipelines, FeatureEngineering, Deployment, Monitoring, Git, CI, CD, Databricks, AWS, Azure, GCP, Cloud, VersionControl 🏢 Description: Responsibilities As a Machine Learning Engineer with a focus on classical ML/deep-learning models, you are responsible for the technical design, implementation, and operation of productive ML solutions. You work in a tandem setup with an internal colleague who handles stakeholder management and overall coordination, allowing you to focus fully on modeling, pipelines, and technical execution. Design, train and optimize classical machine learning and deep-learning models for business-relevant use cases Build and maintain end-to-end machine learning pipelines covering data preparation, feature engineering, training, validation, deployment and monitoring Ensure robustness, performance and reproducibility of machine learning solutions in production environments Implement structured and versioned ML workflows supporting reliable model development and operation Collaborate closely with internal machine learning engineers and data teams on technical topics and solution design Qualifications Successfully completed university degree in Computer Science, Data Science, Mathematics or a related field Solid experience building and operating production-grade machine learning pipelines Strong Python engineering skills , including clean code practices and software engineering best standards Hands-on experience with Git-based version control and working with CI/CD pipelines as a user Experience with productive ML platforms and cloud-based ML environments (e.g. Databricks, AWS, Azure or GCP) Fluent communication skills in English and Polish and availability to work in a hybrid mode with 1–2 office visits per week About OBI Smart Technologies WHO ARE WE: We are a joint venture between OBI and Reply Group, responsible for co-designing, building and operating mission-critical digital platforms for commerce, customer service, and omnichannel retail. OUR MISSION: " We unite technology leadership with deep retail vision to implement standardized processes and scalable digital products that drive efficient support for one of Europe’s largest DIY retailers. Leveraging proven best practices, we advance the internationalization of products and the digital mindset of our partners, delivering consistent and business-critical solutions to support the targets of our customer. "

🏢 Summary: The role focuses on designing, building, and operating production-grade machine learning solutions using classical and deep learning models. You will develop end-to-end ML pipelines, ensure robust and reproducible deployments, and collaborate on technical solution design in a production environment. 🗂️ Requirements: University degree in Computer Science, Data Science, Mathematics or related field, Experience building and operating production-grade machine learning pipelines, Strong Python engineering skills with clean code practices, Experience with Git-based version control, Experience working with CI/CD pipelines, Experience with ML platforms and cloud-based ML environments, Fluent English, Fluent Polish, Availability to work in hybrid mode with 1–2 office visits per week 📃 Skills: Python, Git, CI/CD, Databricks, AWS, Azure, GCP, MachineLearning, DeepLearning 🏢 Description: Responsibilities As a Machine Learning Engineer with a focus on classical ML/deep-learning models, you are responsible for the technical design, implementation, and operation of productive ML solutions. You work in a tandem setup with an internal colleague who handles stakeholder management and overall coordination, allowing you to focus fully on modeling, pipelines, and technical execution. Design, train and optimize classical machine learning and deep-learning models for business-relevant use cases Build and maintain end-to-end machine learning pipelines covering data preparation, feature engineering, training, validation, deployment and monitoring Ensure robustness, performance and reproducibility of machine learning solutions in production environments Implement structured and versioned ML workflows supporting reliable model development and operation Collaborate closely with internal machine learning engineers and data teams on technical topics and solution design Benefits Motivizer Benefits Platform to choose and manage all your benefits in one place. You receive a budget (550 PLN monthly). You can choose medical care package, meal tickets, sports cards (we have Multisport and on preferential terms, we have membership cards to one of the most popular Gyms), cinema tickets, shop vouchers, discounts and many more. Language Courses – you'll have access to a multi-language learning platform enabling you to practice your language skills and learn new ones! Regular and systematic further training opportunities - both internally and from external providers. We support your ongoing learning and development. Cooperation within an internal community is our everyday reality. We have networking events, coding challenges, and company parties for different occasions. Qualifications Successfully completed university degree in Computer Science, Data Science, Mathematics or a related field Solid experience building and operating production-grade machine learning pipelines Strong Python engineering skills , including clean code practices and software engineering best standards Hands-on experience with Git-based version control and working with CI/CD pipelines as a user Experience with productive ML platforms and cloud-based ML environments (e.g. Databricks, AWS, Azure or GCP) Fluent communication skills in English and Polish and availability to work in a hybrid mode with 1–2 office visits per week About OBI Smart Technologies WHO ARE WE: We are a joint venture between OBI and Reply Group, responsible for co-designing, building and operating mission-critical digital platforms for commerce, customer service, and omnichannel retail. OUR MISSION: " We unite technology leadership with deep retail vision to implement standardized processes and scalable digital products that drive efficient support for one of Europe’s largest DIY retailers. Leveraging proven best practices, we advance the internationalization of products and the digital mindset of our partners, delivering consistent and business-critical solutions to support the targets of our customer. "

🏢 Summary: Senior GenAI Engineer role focused on designing and implementing enterprise-grade AI solutions based on LLMs, Agentic AI, and Generative AI. The position involves building end-to-end AI architectures, developing AI/ML pipelines, and integrating intelligent systems with cloud and business platforms. The role also covers MLOps practices and advanced NLP-based solutions including RAG architectures. 🗂️ Requirements: Minimum 3 years experience in Data Science / Machine Learning / Artificial Intelligence, Commercial experience with Generative AI, LLMs or Agentic AI, Very good knowledge of Python, Experience with TensorFlow or PyTorch, Experience with Pandas and Scikit-Learn, Experience with at least one agent framework: LangChain, LangGraph, AutoGen or Semantic Kernel, Knowledge of NLP: tokenization, embeddings, semantic search, RAG architectures, Experience with Azure, AWS or GCP, Knowledge of SDLC 📃 Skills: Python, LLMs, GenerativeAI, AgenticAI, TensorFlow, PyTorch, Pandas, ScikitLearn, LangChain, LangGraph, AutoGen, SemanticKernel, NLP, Tokenization, Embeddings, SemanticSearch, RAG, Azure, AWS, GCP, MLOps, CICD, SDLC 🏢 Description: Poszukujemy doświadczonego Senior GenAI Engineera, który będzie odpowiedzialny za projektowanie i wdrażanie nowoczesnych rozwiązań opartych o LLMs, Agentic AI oraz architektury AI enterprise-grade. Zakres obowiązków Projektowanie i rozwój rozwiązań opartych o: Generative AI / Large Language Models (LLMs) / Agentic AI NLP / intelligent automation oraz AI copilots Tworzenie i wdrażanie architektur AI end-to-end Budowa rozwiązań z wykorzystaniem: LangChain / LangGraph / AutoGen / Semantic Kernel oraz innych frameworków agentowych Implementacja i optymalizacja pipeline’ów AI/ML Rozwój praktyk MLOps: CI/CD / monitoring modeli / deployment / observability Integracja modeli AI z rozwiązaniami biznesowymi i platformami cloud Współpraca z zespołami developerskimi, DevOps oraz biznesowymi Rozwijanie nowych podejść i innowacyjnych rozwiązań AI dla klientów enterprise Wymagania Min. 3 lata doświadczenia w obszarze: Data Science / Machine Learning / Artificial Intelligence Doświadczenie komercyjne w obszarze: Generative AI / LLMs / Agentic AI Bardzo dobra znajomość Python Znajomość frameworków: TensorFlow / PyTorch / Pandas / Scikit-Learn Doświadczenie z przynajmniej jednym frameworkiem: LangChain / LangGraph AutoGen / Semantic Kernel lub podobnym Znajomość NLP: tokenization / embeddings / semantic search / RAG architectures Doświadczenie z Azure, AWS lub GCP Znajomość SDLC Bardzo dobra znajomość języka angielskiego Nice to have Doświadczenie w sektorze automotive i/lub financial services Znajomość: Docker / Kubernetes / Git / Azure DevOps Doświadczenie w MLOps i monitoringu modeli AI Znajomość Trusted / Responsible AI Język niemiecki lub francuski

🏢 Summary: Staff Machine Learning Engineer role focused on leading Generative AI initiatives for manufacturing applications, including multimodal document understanding, structured data extraction, and AI systems combining text, images, and 3D data. The position involves developing and deploying large-scale AI models, shaping technical strategy, and mentoring engineering teams in a cloud-based production environment. 🗂️ Requirements: Bachelor's degree in Computer Science, Machine Learning, AI, or related field, 5+ years of machine learning or data science experience, Expertise in generative models, LLMs, or computer vision, Experience with large-scale language and vision models, Hands-on experience with multimodal data, Proficiency in Python, Experience with PyTorch or TensorFlow, Knowledge of probability, statistics, and optimization, Experience deploying ML models with cloud microservice architecture, Strong software engineering skills, Experience with CI/CD and version control, U.S. Citizen or Green Card holder 📃 Skills: Python, PyTorch, TensorFlow, pandas, NumPy, Transformers, GPT, VLMs, AWS, Terraform, CI/CD, OOP 🏢 Description: Xometry is seeking a Staff Machine Learning Engineer to lead Generative AI efforts focused on real-world manufacturing challenges, including multimodal document understanding, structured data extraction from technical drawings, and reasoning across text, images, and 3D data. Quick Facts - Lead the technical direction for the Generative AI team - Shape the AI roadmap and identify high-value AI opportunities - Develop and deploy large language and generative models - Build multimodal AI systems using text, images, and 3D data - Create scalable data pipelines and training workflows - Deploy models into production using AWS and cloud platforms - Collaborate with engineering, product, and business teams - Mentor teammates on advanced ML methods and best practices - Stay current with generative AI and deep learning research Requirements - Bachelor's degree required; advanced degree in Computer Science, Machine Learning, AI, or related field is a plus - 5+ years of experience in machine learning or data science - Deep expertise in generative models, LLMs, or computer vision - Experience with large-scale language and vision models including Transformers, GPT, and VLMs - Hands-on experience with multimodal data including text, images, and 3D - Proficiency in Python and ML libraries including PyTorch, TensorFlow, pandas, and NumPy - Strong knowledge of probability, statistics, and optimization - Experience deploying ML and AI models using cloud microservice architecture, preferably AWS - Strong software engineering skills including object oriented programming, testing, version control, CI/CD, and IaC with Terraform preferred - Strong communication skills across technical and business stakeholders - U.S. Citizen or Green Card holder required for ITAR compliance Benefits - 401(k) match - Medical, dental, and vision insurance - Life and disability insurance - Generous paid time off - Vacation, sick leave, floating and fixed holidays - Maternity and bonding leave - Employee assistance program and wellbeing resources Xometry is an equal opportunity employer. For U.S.-based roles, the company participates in E-Verify and will use Form I-9 information to confirm work authorization after acceptance of a job offer.

🏢 Summary: The offer is for an MLOps / AI Engineer to design, implement and maintain AI/ML solutions for banking and financial sector projects. The role focuses on building MLOps environments, automating training and deployment processes, and managing cloud-based AI infrastructure in production. You will support the full lifecycle of ML models, including monitoring and optimization in production environments. 🗂️ Requirements: 3–4 years of experience as MLOps Engineer, AI Engineer, Machine Learning Engineer or similar, Strong knowledge of Python, Experience building and maintaining ML solutions in production environments, Experience with Docker and containerization, Experience with AWS, Azure or Google Cloud Platform, Knowledge of CI/CD and deployment automation, Experience working with Git, Knowledge of AI/ML model monitoring in production 📃 Skills: Python, Docker, AWS, Azure, GCP, CICD, Git, MLOps, MachineLearning, Monitoring, Cloud 🏢 Description: O projekcie Poszukujemy MLOps / AI Engineera do realizacji innowacyjnych projektów dla sektora bankowego i finansowego. Osoba na tym stanowisku będzie odpowiedzialna za projektowanie, wdrażanie oraz utrzymanie rozwiązań opartych o sztuczną inteligencję, uczenie maszynowe oraz nowoczesne platformy danych. Będziesz współpracować z zespołami Data Science, Data Engineering i DevOps, wspierając cały cykl życia modeli AI – od budowy środowisk treningowych po wdrożenie modeli na środowiska produkcyjne. Twój zakres obowiązków Projektowanie i rozwój środowisk MLOps wspierających wdrażanie modeli AI/ML Automatyzacja procesów trenowania, testowania oraz wdrażania modeli Budowa i utrzymanie pipeline'ów ML oraz Data Pipelines Monitorowanie jakości, wydajności i stabilności modeli produkcyjnych Współpraca z Data Scientistami oraz zespołami developerskimi Implementacja rozwiązań opartych o Generative AI i Large Language Models (LLM) Zarządzanie infrastrukturą chmurową wspierającą rozwiązania AI Tworzenie dokumentacji technicznej oraz dobrych praktyk w zakresie AI Engineering Optymalizacja kosztów i wydajności środowisk AI/ML Nasze wymagania Minimum 3–4 lata doświadczenia na stanowisku MLOps Engineer, AI Engineer, Machine Learning Engineer lub pokrewnym Bardzo dobra znajomość Python Doświadczenie w budowie i utrzymaniu rozwiązań Machine Learning w środowiskach produkcyjnych Znajomość Docker oraz konteneryzacji aplikacji Doświadczenie z platformami chmurowymi AWS, Azure lub Google Cloud Platform Znajomość CI/CD oraz automatyzacji procesów wdrożeniowych Doświadczenie w pracy z Git Znajomość zagadnień związanych z monitoringiem modeli AI Umiejętność współpracy z zespołami Data Science i Engineering Znajomość języka angielskiego na poziomie B2–C1 Mile widziane Doświadczenie z MLflow Znajomość Apache Airflow Doświadczenie z Kubernetes Praktyczna znajomość PyTorch lub TensorFlow Doświadczenie z Large Language Models (LLM) Znajomość frameworków takich jak LangChain, LangGraph lub LlamaIndex Doświadczenie z bazami wektorowymi (Pinecone, Weaviate, ChromaDB, Qdrant) Znajomość rozwiązań RAG (Retrieval-Augmented Generation) Doświadczenie w projektach Generative AI Znajomość Apache Kafka Doświadczenie w sektorze bankowym lub finansowym Oferujemy Udział w nowoczesnych projektach związanych ze sztuczną inteligencją i uczeniem maszynowym Możliwość pracy zdalnej lub hybrydowej Elastyczne godziny pracy Stabilną współpracę przy długoterminowych projektach Możliwość rozwoju kompetencji w obszarze AI, MLOps i Generative AI Pracę z najnowszymi technologiami chmurowymi i rozwiązaniami AI Współpracę z ekspertami Data Science, AI oraz Cloud Engineering Realny wpływ na rozwój innowacyjnych produktów i usług Atrakcyjne wynagrodzenie adekwatne do doświadczenia i kompetencji Jeżeli chcesz rozwijać rozwiązania oparte na sztucznej inteligencji, wdrażać modele ML na skalę produkcyjną oraz uczestniczyć w projektach wykorzystujących Generative AI i LLM – zapraszamy do aplikowania.

🏢 Summary: The role focuses on engineering production-grade AI features such as semantic search, intelligent assistants, and automated risk scoring by integrating external AI providers into a cybersecurity platform. You will own the full lifecycle from prototype to reliable, monitored production services, primarily using Python on Azure. This position emphasizes robust software engineering practices over model research or training. 🗂️ Requirements: 5+ years of professional experience building production systems in Python, Expert-level Python programming skills, Experience with ML frameworks and libraries, Proven experience shipping and operating production software, Experience integrating external APIs in production environments, Strong understanding of software architecture and design patterns, Practical experience with CI/CD pipelines, Experience with containerization using Docker, Understanding of AI/ML concepts including LLMs, embeddings, prompt engineering, RAG, Experience with unit and integration testing and mocking external services, Polish work permit, Professional proficiency in English 📃 Skills: Python, Azure, OpenAI, Anthropic, Docker, CI/CD, FastAPI, Flask, Pinecone, Weaviate, Chroma, .NET, REST, LLMs, RAG, Embeddings, Git 🏢 Description: About the Role As a Senior AI/ML Engineer you will be building AI-powered features at the core of our platform - semantic search, an intelligent assistant, automated risk scoring, and much more. We mainly integrate with external AI model providers (OpenAI, Anthropic, and others) to deliver these capabilities to our clients and internal users. This is a software engineering role, not a data science or ML research position. You won't train models from scratch or publish papers. You'll engineer production-grade systems that leverage AI to solve real cybersecurity problems. If you're a strong Python engineer excited about making AI reliable, maintainable, and impactful — we want to talk to you. We're looking for a versatile software engineer to own the journey from AI prototype to reliable production system: building robust integrations with external AI providers or fine-tuned models, standardizing our Python codebase and release pipelines, and ensuring our AI features meet the same quality bar as any other production service. What You'll Do Ship AI features end to end - from integration design through deployment to monitoring in production. You'll build and maintain Python services that power our AI-driven capabilities on Azure. Build production-ready AI / ML integrations - including retry logic, rate limiting, cost monitoring, fallback strategies, and abstraction layers that allow us to swap between model providers. Turn proofs of concept into reliable software - collaborate with our AI experts (who bring deep ML/data science expertise) to take working prototypes and engineer them into tested, documented, production-grade services. Standardize Python engineering practices - establish and evolve our code organization, testing strategies, CI/CD pipelines, and release processes for AI/ML features. Design clean service boundaries - our platform's core runs on .NET. You'll design and maintain well-defined APIs between the Python/AI layer and the rest of the system. Mentor and share knowledge - help other engineers grow their Python and AI engineering skills, and bring engineering rigor to the broader team's practices. Contribute to architecture decisions - work closely with other teams to shape how AI capabilities evolve within the platform. Who You Are Must-Haves 🔹 5+ years of professional experience building and maintaining production systems in Python. 🔹 Expert-level programming skills and proficiency with common ML frameworks and libraries. 🔹 A track record of shipping and operating software - not just building prototypes. You care about testing, monitoring, logging, and what happens after deployment. 🔹 Experience integrating external APIs in production systems - ideally AI/LLM provider APIs (OpenAI, Anthropic, Azure AI, or similar), but strong API integration experience in any domain counts. 🔹 Solid understanding of software architecture and design patterns - you have opinions about how to structure a Python project and can articulate trade-offs. 🔹 Practical knowledge of CI/CD pipelines, containerization (Docker), and modern development workflows. 🔹 A working understanding of AI/ML concepts - you know what embeddings, LLMs, prompt engineering, and RAG are. You can have a productive technical conversation with an ML specialist without needing every concept explained from scratch. 🔹 Experience with testing strategies - unit tests, integration tests, mocking external services. You instinctively write tests, not as an afterthought. 🔹 A highly adaptable, problem-solving and result-oriented mindset with the ability to work independently and take ownership in a fast-paced and dynamic environment. 🔹 Strong communication skills in English (our working language). 🔹 Willingness to learn continuously and share what you learn with the team. Nice-to-Haves 🔸 Experience with Azure cloud services. 🔸 Familiarity with FastAPI, Flask, or similar Python web frameworks. 🔸 Exposure to MLOps tooling or practices (model versioning, experiment tracking, feature stores). 🔸 Hands-on experience in Document AI / Intelligent Document Processing using traditional models and Generative AI. 🔸 Experience with vector databases (Pinecone, Weaviate, Chroma, or similar). 🔸 Any experience with .NET - helpful for cross-team collaboration, but not expected. 🔸 Background in or interest in cybersecurity as a domain. Your Team You'll join our Synapse team - a small, focused group responsible for all AI/ML capabilities within our platform. The team consists of: -> Team Leader / Architect - provides high-level architectural guidance, planning, and cross-stack delivery. -> AI / ML Engineer - deep expertise in AI/ML and data science. Your counterbalance: they bring the ML knowledge, you bring the production engineering discipline. -> AI / Backend Engineer - transitioning from .NET into AI engineering. A teammate you'll mentor and grow alongside. -> You - the person who bridges the gap between AI prototypes and reliable production systems. Why Join Us? / What We Offer: Competitive salary and benefits package. Remote work options and flexible working hours. Actual impact on the choice and shape of solutions developed. Opportunities for professional growth and development. Training and conference budget. A collaborative, innovative work environment with an iterative agile approach. The role is for six months with the possibility of extension. Both full-time and part-time cooperation are possible.

🏢 Summary: Senior Lead AI/ML Engineer role focused on building and operating AI-native security tooling integrated with Azure and GitHub Copilot. The position involves hands-on development of deterministic orchestration systems, multi-agent workflows, and secure SDLC practices across the full lifecycle. The engineer will design, develop, test, deploy, and integrate AI-driven solutions within vulnerability-response environments. 🗂️ Requirements: Senior-level hands-on engineering experience with daily production code delivery, Deep experience with Azure and GitHub Copilot as primary stack, Strong proficiency in Go or equivalent systems language, Hands-on experience with multi-agent and multi-model workflows in production, Experience with secure SDLC, TDD, and threat modeling, Full SDLC ownership from design through deployment and documentation 📃 Skills: Azure, GitHub, Copilot, Go, Kubernetes, Kibana, Python, PySpark, SAS, SPSS, TensorFlow, PyTorch, Scikit-learn, CNTK, Keras, MXNet, R, Kubeflow, BentoML, SIEM, SOAR, EDR, ITSM, CMDB 🏢 Description: Senior Lead AI/ML Engineer Primary Skills Value Quantification: Pre-Model Development, Model Provisioning: Kubernetes, Kibana, Model Monitoring, Cloud Computing, Python/PySpark, SAS/SPSS, Great Expectation, Evidently AI, Deployment Strategies (A/B, Blue green, Canary), Model testing, Tools (KubeFlow, BentoML), Integration testing, ML Frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet), Value Quantification: Post-Model Deployment, Model Experimentation, R/R Studio Specialization ML Engineering: AI/ML Engineer Job Requirements Senior Lead AI/Full Stack Engineer Work Type: Hybrid Model with min 2–3 days per week Description The mission is to build AI-native tooling that enables rapid, machine-speed response to security threats by implementing work-focused security agents and deterministic orchestration integrated with vulnerability-response stacks (SIEM/SOAR/EDR, identity, vulnerability management, CMDB, ITSM). This is a hands-on engineering role focused on writing production code, operating agent fleets, and delivering across the full SDLC. Responsibilities - Write production-grade code, primarily in Go, building deterministic and testable orchestration tooling. - Operate multi-agent workflows, decomposing backlogs into parallel streams and managing review gates. - Embed security into development with TDD, validation stages, persona-based threat judging, signed builds, SBOMs, and strict access control. - Integrate natively with Azure and GitHub Copilot; build missing components within the existing stack. - Run model-agnostic personas across Claude, Copilot, and ChatGPT, managing token usage and context budgets. - Own end-to-end SDLC: design, development, testing, integration, deployment, documentation, and knowledge transfer. Must-have - Senior engineer actively delivering hands-on production code. - Deep Azure and GitHub Copilot delivery experience. - Strong Go or equivalent systems language expertise. - Proven experience operating multi-agent or multi-model workflows in production. - Strong secure SDLC practices, TDD discipline, and threat modeling experience. - End-to-end SDLC ownership experience. Nice-to-have - Experience integrating SIEM, SOAR, EDR, identity, vulnerability management, CMDB, or ITSM systems. - Experience with evaluation harnesses, red-teaming, agent guardrails, sandboxing, reversibility, confidence thresholds, and audit trails.