Senior Python Developer

Join to apply for the Senior Python Developer (with ML) role at Intellectsoft3 weeks ago Be among the first 25 applicants

Join to apply for the Senior Python Developer (with ML) role at IntellectsoftIntellectsoft 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 growth and scalability.

Our clients include Jaguar Motors, Universal Pictures, Harley-Davidson, Qualcomm, and London Stock Exchange. Together, our team delivers solutions that make a difference. Learn more at

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. Requirements5+ years of experience in backend software development with a focus on building scalable and maintainable solutions

Strong programming skills in Python, with a deep understanding of writing clean, efficient, and well-structured code

Experience with web frameworks, including FastAPI and developing RESTful APIsProficiency in version control using Git and maintaining structured pull requests

Test-Driven Development (TDD) experience: writing unit tests with Pytest and implementing integration tests to ensure robustness and reliability

Experience with CI/CD pipelines and automated deployment practices

Familiarity with DevOps concepts, including containerization (e.g., Docker), orchestration (e.g., Kubernetes), and cloud infrastructure management (AWS, Azure, GCP)Experience in data engineering within Big Data ecosystems, including data pipelines and data integration

Solid understanding of software architecture and system design for high-availability applications

Knowledge of fundamental computer science concepts, including data structures, algorithms, and problem-solving

Excellent communication skills and ability to work collaboratively within cross-functional teams

Proficiency in English, both written and spoken

Nice to have skills

Experience with Machine Learning (ML): deploying and managing models, creating inference pipelines, and ML Ops practices

Knowledge of ML platforms such as Airflow, SageMaker, Kubeflow, or MLFlowExperience with distributed computing (e.g., Spark/PySpark)Understanding of cloud ML deployment and model serving on platforms like AWS, Azure, or GCPExperience with Large Language Models (LLMs), model fine-tuning, and Retrieval-Augmented Generation (RAG) pipelines

Experience in developing enterprise-grade applications that leverage data-driven decision-makingResponsibilitiesDevelop, maintain, and optimize backend services and APIs using Python, ensuring high performance and scalability

Design and implement data processing pipelines to handle large volumes of data efficiently

Collaborate with cross-functional teams to understand client needs and translate them into practical features

Write clean, testable, and maintainable code, following best practices and coding standards

Ensure code quality through code reviews, unit testing (using Pytest), and integration testing

Implement and maintain CI/CD pipelines, and ensure smooth deployment processes

Integrate and manage cloud-based solutions and infrastructure (e.g., AWS, Azure, GCP)Utilize DevOps tools and practices for containerization and orchestration (Docker, Kubernetes)Monitor application performance, identify bottlenecks, and implement improvements

Participate in team meetings, providing updates on progress and discussing upcoming tasks

Utilize issue tracking and version control systems (like Git) to maintain high-quality software development processes

Stay updated on the latest technologies and apply innovative solutions where applicable

Nice-to-Have Responsibilities (ML Focus):Develop, refine, and utilize ML engineering platforms and components as needed

Establish and manage processes for data preparation, feature engineering, and prediction

Closely monitor model performance and address any issues that arise

Explore opportunities to integrate ML workflows into backend systems when it adds value

Stay informed about ML Ops practices and maintain pipelines for training and inferenceBenefits35 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

Seniority level

Seniority level

Mid-Senior level

Employment type

Employment type

Full-time

Job function

Job function

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