Ciklum is looking for a Senior Artificial Intelligence/Machine Learning Engineer to join our team full-time in Romania. We are a custom product engineering company that supports both multinational organizations and scaling startups to solve their most complex business challenges. With a global team of over 4,000 highly skilled developers, consultants, analysts and product owners, we engineer technology that redefines industries and shapes the way people live. About the role: As a Senior Artificial Intelligence/Machine Learning Engineer you will take a leadership role in shaping the strategic direction of our machine learning infrastructure, proactively identifying opportunities for innovation and improvement. You will drive the development of cutting-edge solutions that enhance the performance, scalability, and reliability of our machine learning systems. In collaboration with the Data Science team, you will ensure that models are deployed seamlessly, optimised for production environments, and meet the highest standards of efficiency and accuracy at scale. You will also be responsible for architecting and overseeing the development of complex machine learning pipelines, managing both real-time and batch inference systems that are integral to our predictive platforms. You will work closely with cross-functional teams to anticipate future needs, recommending and implementing long-term solutions that align with our business objectives. As a senior member of the team, you will mentor and guide mid-level Machine Learning Engineers, providing technical leadership and helping to shape best practices across the organisation. Your expertise will play a key role in conducting comprehensive code reviews, identifying areas for improvement, and fostering a culture of continuous learning and collaboration. Let's empower our global Artificial Intelligence/Machine Learning influence together! Responsibilities: - As a senior member of the team, you will mentor and guide mid-level Machine Learning Engineers, providing technical leadership and helping to shape best practices across the organisation. Your expertise will play a key role in conducting comprehensive code reviews, identifying areas for improvement, and fostering a culture of continuous learning and collaboration - Beyond technical execution, you will be expected to communicate effectively with both technical and non-technical stakeholders, translating complex machine learning concepts into actionable business insights. You will present innovative solutions to key stakeholders, making compelling cases for new initiatives and guiding the strategic direction of our machine learning efforts - Finally, you will lead the integration of new technologies and tools into our infrastructure, staying ahead of industry trends and ensuring that our machine learning frameworks remain at the cutting edge of technological advancements Requirements: - Expert-level proficiency with cloud technologies (ideally AWS) and extensive experience with containerization and orchestration (preferably Kubernetes) - Deep understanding of software development, DevOps, and MLOps best practices, with a proven track record of applying them in production - Extensive experience in designing, deploying, and maintaining scalable models and services in production environments - Strong understanding of Machine Learning, with the ability to collaborate deeply with Data Scientists on model deployment and optimization - Experience with MLflow for experiment tracking and model management, and Airflow or Dagster for orchestrating end-to-end ML pipelines and workflows - Significant experience with Data Engineering, Kafka, and stream processing - Proficiency in Python and SQL; or any other programming languages is a strong plus What`s in it for you? - Strong community: Work alongside top professionals in a friendly, open-door environment - Growth focus: Take on large-scale projects with a global impact and expand your expertise - Tailored learning: Boost your skills with internal events (meetups, conferences, workshops), Udemy access, language courses, and company-paid certifications - Endless opportunities: Explore diverse domains through internal mobility, finding the best fit to gain hands-on experience with cutting-edge technologies - Enjoy radical flexibility – work remotely or from an office, your choice - Care: Medical subscription to Regina Maria, meal tickets of 16 ron net/day worked About us: At Ciklum, we are always exploring innovations, empowering each other to achieve more, and engineering solutions that matter. With us, you’ll work with cutting-edge technologies, contribute to impactful projects, and be part of a One Team culture that values collaboration and progress. In Romania, we welcome top-tier tech talent — whether from our Bucharest office or fully remotely. Tap into deep industry knowledge, grow your career, and make an impact in an empowering environment. Want to learn more about us? Follow us on Instagram, Facebook, LinkedIn. Explore, empower, engineer with Ciklum! Interested already? We would love to get to know you! Submit your application. We can’t wait to see you at Ciklum.

Ciklum is looking for a Senior Artificial Intelligence/Machine Learning Engineer to join our team full-time in Bulgaria. We are a custom product engineering company that supports both multinational organizations and scaling startups to solve their most complex business challenges. With a global team of over 4,000 highly skilled developers, consultants, analysts and product owners, we engineer technology that redefines industries and shapes the way people live. About the role: As a Senior Artificial Intelligence/Machine Learning Engineer you will take a leadership role in shaping the strategic direction of our machine learning infrastructure, proactively identifying opportunities for innovation and improvement. You will drive the development of cutting-edge solutions that enhance the performance, scalability, and reliability of our machine learning systems. In collaboration with the Data Science team, you will ensure that models are deployed seamlessly, optimised for production environments, and meet the highest standards of efficiency and accuracy at scale. You will also be responsible for architecting and overseeing the development of complex machine learning pipelines, managing both real-time and batch inference systems that are integral to our predictive platforms. You will work closely with cross-functional teams to anticipate future needs, recommending and implementing long-term solutions that align with our business objectives. As a senior member of the team, you will mentor and guide mid-level Machine Learning Engineers, providing technical leadership and helping to shape best practices across the organisation. Your expertise will play a key role in conducting comprehensive code reviews, identifying areas for improvement, and fostering a culture of continuous learning and collaboration. Let's empower our global Artificial Intelligence/Machine Learning influence together! Responsibilities: - As a senior member of the team, you will mentor and guide mid-level Machine Learning Engineers, providing technical leadership and helping to shape best practices across the organisation. Your expertise will play a key role in conducting comprehensive code reviews, identifying areas for improvement, and fostering a culture of continuous learning and collaboration - Beyond technical execution, you will be expected to communicate effectively with both technical and non-technical stakeholders, translating complex machine learning concepts into actionable business insights. You will present innovative solutions to key stakeholders, making compelling cases for new initiatives and guiding the strategic direction of our machine learning efforts - Finally, you will lead the integration of new technologies and tools into our infrastructure, staying ahead of industry trends and ensuring that our machine learning frameworks remain at the cutting edge of technological advancements Requirements: - Expert-level proficiency with cloud technologies (ideally AWS) and extensive experience with containerization and orchestration (preferably Kubernetes) - Deep understanding of software development, DevOps, and MLOps best practices, with a proven track record of applying them in production - Extensive experience in designing, deploying, and maintaining scalable models and services in production environments - Strong understanding of Machine Learning, with the ability to collaborate deeply with Data Scientists on model deployment and optimization - Experience with MLflow for experiment tracking and model management, and Airflow or Dagster for orchestrating end-to-end ML pipelines and workflows - Significant experience with Data Engineering, Kafka, and stream processing - Proficiency in Python and SQL; or any other programming languages is a strong plus What`s in it for you? - Regular salary reviews based on performance - Corporate events: webinars, offline parties, and meetups - Internal Mobility Program - Tailored education path (including full access to Udemy, certifications, etc.) - 25 paid days off: 20 business days of vacation per calendar year + 5 undocumented sick leave days - Additional health insurance - 100% company-covered Multisport card, with discounts available for family members About us: At Ciklum, we are always exploring innovations, empowering each other to achieve more, and engineering solutions that matter. With us, you’ll work with cutting-edge technologies, contribute to impactful projects, and be part of a One Team culture that values collaboration and progress. Since expanding to Bulgaria in 2022, we’ve been building a fast-growing team that thrives on learning, collaboration, and innovation. Join us on this exciting journey and help shape the future of our delivery center. Want to learn more about us? Follow us on Instagram, Facebook, LinkedIn. Explore, empower, engineer with Ciklum! Interested already? We would love to get to know you! Submit your application. We can’t wait to see you at Ciklum.

• Design and implement scalable ML infrastructure to support model development and deployment • Develop and maintain evaluation frameworks for Large Language Models (LLMs), including RAG-based systems • Evaluate model performance using tools such as RAGAS, DeepEval, or similar frameworks • Contribute to the development of GenAI and Agentic AI solutions • Build and enhance monitoring systems for ML models in production environments • Collaborate with cross-functional teams including data scientists, engineers, and product stakeholders • Apply best practices in model versioning, testing, and deployment pipelines • Optimize performance, scalability, and cost efficiency in cloud environments

• Design, develop, fine-tune, and evaluate machine learning, deep learning, and Generative AI models, including Large Language Models (LLMs). • Apply appropriate modeling techniques (supervised, unsupervised, NLP, deep learning) based on problem context and data constraints. • Optimize model performance across accuracy, latency, scalability, and cost dimensions. • Conduct rigorous model evaluation, validation, and benchmarking using large-scale datasets. • Apply data preprocessing, feature engineering, augmentation, and synthetic data generation techniques to improve model robustness. • Design and implement scalable, production-ready AI solutions integrated into existing platforms and workflows. • Build, maintain, and improve MLOps pipelines for model training, deployment, monitoring, and lifecycle management. • Deploy and manage AI applications in cloud environments (Azure, AWS, or GCP), including containerization and orchestration where applicable. • Monitor model performance in production; identify drift, degradation, or failures and implement remediation strategies. • Troubleshoot and resolve AI/ML engineering issues across development and production environments. • Partner with Product Managers, Product Owners, Software Engineers, Data Scientists, and Research teams to align AI solutions with business and product objectives. • Translate product requirements and use cases into technical architectures and model designs. • Support integration of AI capabilities into customer-facing products and internal platforms. • Communicate technical concepts, tradeoffs, and limitations clearly to non-technical stakeholders. • Work with structured and unstructured datasets, including healthcare, claims, and life sciences data, to build high-performance AI systems. • Ensure responsible handling, transformation, and validation of data used for model training and inference. • Collaborate with data engineering and QA teams to ensure data pipelines and AI workflows are production-ready and auditable. • Stay current with advances in Generative AI, LLM architectures, model fine-tuning techniques, and applied machine learning. • Contribute to internal best practices, standards, and reusable components for AI/ML development. • Document AI/ML workflows, architectures, methodologies, and lessons learned for internal knowledge sharing. • Proactively identify opportunities to improve scalability, reliability, and efficiency of existing AI systems.