Senior Applied AI Developer (IR-444)

Intellectsoft is a software development company delivering innovative solutions since 2007. We operate across North America, Latin America, the Nordic region, the UK, and Europe.We specialize in industries like Fintech, Healthcare, EdTech, Construction, Hospitality, and more, partnering with startups, mid-sized businesses, and Fortune 500 companies to drive innovation and scalability. Our clients include Jaguar Motors, Universal Pictures, Harley-Davidson, and many more where our teams are making daily impactTogether, our team delivers solutions that make a difference. Learn more at www.intellectsoft.net Our customer's product is an AI-powered platform that helps businesses make better decisions and work more efficiently. It uses advanced analytics and machine learning to analyze large amounts of data and provide useful insights and predictions. The platform is widely used in various industries, including healthcare, to optimize processes, improve customer experiences, and support innovation. It integrates easily with existing systems, making it easier for teams to make quick, data-driven decisions to deliver cutting-edge solutions. Requirements 5+ years of practical experience in Machine Learning. Solid understanding of ML and Deep Learning fundamentals, including model fine-tuning (especially LLMs). Proficient in Python; experience with PySpark or Scala is a plus. Background in backend API development and working with vector databases. Experience with ML Ops practices such as model monitoring, tracking KPIs, and managing model drift (preferably using MLflow). Hands-on experience with NLP or computer vision projects. Familiarity with ML frameworks such as Keras or HuggingFace. Experience in building feature engineering pipelines, inference workflows, and deploying models for real-time predictions. Nice to have Exposure to Big Data systems and data engineering practices. Knowledge of cloud platforms and architecture, with an understanding of CI/CD pipelines and DevOps practices. Awareness of modern AI/ML trends, especially in Generative AI and Large Language Models. Experience designing scalable ML systems that handle large datasets and meet strict performance SLAs. Responsibilities Develop and maintain ML engineering platforms and reusable components. Deploy ML models and implement feedback loops to monitor and improve their performance in production. Build robust, testable, and scalable code that meets high quality standards and accounts for potential edge cases. Collaborate with client-facing teams to gather technical requirements and align solutions with business needs. Participate in agile development ceremonies (e.g., scrum meetings) and clearly communicate progress, blockers, and dependencies. Contribute to code reviews, version control practices, and bug tracking processes. Conduct research and develop prototypes to evaluate emerging tools, frameworks, and architectures. Benefits 35 absence days per year for work-life balance Udemy courses of your choice English courses with native-speaker Regular soft-skills trainings Excellence Сenters meetups Online/offline team-buildings Originally posted on Himalayas