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.

Who we are At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences. Our dedication to remote-first work, and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands. We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions! . See yourself at Twilio Join the team as Twilio’s next Staff Machine Learning Engineer. About the job This position is needed to scope, design, and deploy machine learning systems into the real world, the individual will closely partner with Product & Engineering teams to execute the roadmap for Twilio’s AI/ML products and services. You will understand customers need, build data products that works at a global scale and own end-to-end execution of large scale ML solutions. To thrive in this role, you must have a deep background in ML engineering, and a consistent track record of solving data & machine-learning problems at scale. You are a self-starter, embody a growth attitude, and collaborate effectively across organizations. Responsibilities In this role, you’ll: - Build and maintain scalable machine learning solutions in production - Train and validate both deep learning-based and statistical-based models considering use-case, complexity, performance, and robustness - Demonstrate end-to-end understanding of applications and develop a deep understanding of the “why” behind our models & systems - Partner with product managers, tech leads, and stakeholders to analyze business problems, clarify requirements and define the scope of the systems needed - Work closely with data platform teams to build robust scalable batch and realtime data pipelines - Collaborate with software engineers, build tools to enhance productivity and to ship and maintain ML models - Drive high engineering standards on the team through mentoring and knowledge sharing - Uphold engineering best practices around code reviews, automated testing and monitoring Qualifications Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table! Required: - 7+ years of applied ML experience with proficiency in Python - Strong background in the foundations of Machine Learning and building blocks of modern Deep Learning - Track record of building, shipping and maintaining Machine Learning models in production in an ambiguous and fast paced environment. - Track record of designing and architecting large scale experiments and analysis to inform product roadmap. - You have a clear understanding of frameworks like - PyTorch, TensorFlow, or Keras, why and how these frameworks do what they do - Familiarity with ML Ops concepts related to testing and maintaining models in production such as testing, retraining, and monitoring. - Demonstrated ability to ramp up, understand, and operate effectively in new application / business domains. - You’ve explored modern data storage, messaging, and processing tools (Kafka, Apache Spark, Hadoop, Presto, DynamoDB etc.) and demonstrated experience designing and coding in big-data components such as DynamoDB or similar - Experience working in an agile team environment with changing priorities - Experience of working on AWS Desired: - Experience with Large Language Models Location This role will be remote, and based in India Travel We prioritize connection and opportunities to build relationships with our customers and each other. For this role, you may be required to travel occasionally to participate in project or team in-person meetings. What We Offer Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location. Twilio thinks big. Do you? We like to solve problems, take initiative, pitch in when needed, and are always up for trying new things. That's why we seek out colleagues who embody our values — something we call Twilio Magic. Additionally, we empower employees to build positive change in their communities by supporting their volunteering and donation efforts. So, if you're ready to unleash your full potential, do your best work, and be the best version of yourself, apply now! If this role isn't what you're looking for, please consider other open positions. Twilio is proud to be an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Additionally, Twilio participates in the E-Verify program in certain locations, as required by law.