Company Background Our client is a leading global provider of advanced analytics, technology solutions, and clinical research services for the life sciences industry. The company combines large-scale healthcare data with AI-powered analytics to accelerate drug development, clinical trials, and commercialization for pharmaceutical and biotech companies. It was named to Fortune’s World’s Most Admired Companies list in 2026. Project Description Project is seeking a hands-on AI Engineer to design, build, and deploy production-ready AI and machine learning systems. The engineer will work closely with data scientists, architects, and product teams to transform models and AI concepts into scalable, reliable applications. The role combines AI/ML engineering, production deployment, and application integration to help deliver practical AI-driven solutions. Technologies Python / TypeScript / C# PyTorch / TensorFlow / Scikit-learn REST APIs, microservices Azure / AWS / GCP CI/CD, MLOps, model monitoring What You'll Do Design, develop, train, and deploy machine learning and deep learning models for production use; Build and maintain end-to-end AI/ML pipelines, covering data preparation, model development, deployment, monitoring, and continuous improvement; Integrate AI capabilities into applications through APIs, microservices, and scalable backend services; Work with LLMs, RAG pipelines, and AI agents where relevant to product needs; Optimize models and AI services for performance, scalability, latency, and cost efficiency; Implement and improve CI/CD and MLOps practices to automate the model lifecycle; Monitor models and AI services in production, ensuring reliability, accuracy, and stable performance; Collaborate with data scientists, software engineers, DevOps/MLOps engineers, and product teams to deliver AI-driven features; Job Requirements Strong programming skills in Python and/or TypeScript/C#; Experience with ML frameworks such as PyTorch, TensorFlow, or Scikit-learn; Hands-on experience deploying AI/ML models to production environments; Experience building or integrating APIs, microservices, and distributed systems; Familiarity with cloud platforms such as Azure, AWS, or GCP; Understanding of MLOps practices, including CI/CD, model monitoring, versioning, and automated deployment; English level: B2 or higher; Nice To Have Experience with Generative AI, LLMs, or RAG architectures; Familiarity with vector databases such as Pinecone, Weaviate, or similar tools; Understanding of data pipelines and streaming systems; Experience with model evaluation frameworks; What Do We Offer The global benefits package includes: Technical and non-technical training for professional and personal growth; Internal conferences and meetups to learn from industry experts; Support and mentorship from an experienced employee to help you professional grow and development; Health insurance; English courses; Sports activities to promote a healthy lifestyle; Flexible work options, including remote and hybrid opportunities; Referral program for bringing in new talent; Work anniversary program and additional vacation days.