Software Engineer (Python & MLOps) at IT Labs

, , Serbia -

Full Time

Start Date

Immediate

Expiry Date

21 Dec, 25

Salary

0.0

Posted On

22 Sep, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, FastAPI, REST APIs, MLOps, AWS Cloud Services, Unit Testing, Integration Testing, End-To-End Testing, Cloud Engineering, Backend Development, Software Engineering, OOP Principles, Prototyping, Developer Platforms, Kubernetes, Containerization

Industry

Software Development

Description

We are seeking a versatile Software Engineer with strong expertise in Python backend development, cloud engineering, and exposure to machine learning workflows. This role is central to bridging the work between machine learning teams and platform engineering, ensuring smooth integration between models, backend systems, and infrastructure. You will play a key role in building and maintaining backend solutions using FastAPI, developing APIs and SDKs that follow best practices, and enabling seamless data exchange between services and machine learning models. Beyond backend engineering, you will support MLOps processes, explore new tools and libraries, and contribute to internal developer platforms that empower ML engineers to iterate and deploy faster. The role is highly dynamic — you’ll often work in isolated environments to research, prototype, and implement new concepts that improve workflows, infrastructure, or deployment pipelines. Responsibilities: Design, develop, and maintain backend solutions in Python (with FastAPI and REST APIs). Enable communication between backend systems and machine learning models. Act as the technical bridge between ML-focused teams and platform engineering. Apply solid OOP and programming principles to deliver clean, maintainable code. Implement and maintain unit and end-to-end testing across all services. Research and quickly prototype new tools, libraries, and frameworks to improve workflows. Support internal developer platforms used by ML engineers to experiment and deploy models efficiently. Collaborate with cloud and platform engineers on AWS-based deployments, Helm chart updates, and GitHub workflows. Strong background in software engineering and backend development. Proficiency in Python and FastAPI. Hands-on experience with REST API development and best practices. Solid understanding of MLOps workflows and practical experience integrating ML models into production environments. Strong knowledge of AWS Cloud Services. Experience with testing frameworks and principles (unit, integration, end-to-end). Familiarity with Unix-like operating systems. Nice to Have: Experience with Kubernetes, containerization, and Kubeflow. Experience with Helm charts, GitHub Actions/Workflows, and cloud-native CI/CD. Knowledge of local Kubernetes environments. (e.g. Minikube) Long-term 12 month contract, Full-time Choose your contract: Contract or B2B, 10 Days PTO after 4 months of working in IT Labs, Referral Bonuses, Working on international projects, Virtual Knowledge Sharing Sessions, Events and team hangouts. Our values We are a company that seeks the best for both our employees and clients, reaching beyond expectations in turning dreams into reality. Our way of working is rooted in our core values (Integrity, Excellence, Proactivity, Innovation, and People), with an expectation that our future colleagues will make these their second nature in their everyday work and life. We don’t ask for perfection, but we do appreciate people motivated to better themselves in every conceivable aspect. About IT Labs Founded in 2005, IT Labs is an international software tech company, specializing in purpose and process-driven teams for high-performance, innovation, transformation, and efficiency. Our HQ is in Palm Beach Gardens, Florida, and we have teams and offices around the world - the US, the UK, the Netherlands, Argentina, Brazil, Serbia, and North Macedonia. We are constantly growing, and we would love for you to become part of our team!

Responsibilities

Design, develop, and maintain backend solutions in Python using FastAPI and REST APIs. Act as the technical bridge between machine learning teams and platform engineering to ensure smooth integration of models and backend systems.