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- Tasks: Develop and optimize Python microservices using FastAPI and integrate AI/ML models.
- Company: Join a government-funded non-profit focused on an innovative AI-driven platform.
- Benefits: Enjoy flexible hybrid work, competitive day rates, and exposure to cutting-edge technologies.
- Why this job: Make a real-world impact while working with modern cloud and AI technologies in an Agile team.
- Qualifications: Strong Python skills, experience with FastAPI, and familiarity with cloud deployments are essential.
- Other info: Contract length is 6 months with possible extension; outside IR35.
The predicted salary is between 48000 - 72000 £ per year.
Job Description
Senior Python Engineer – FastAPI, AI/ML & Cloud (Outside IR35, Hybrid, London)
Location: Hybrid – London Office
Day Rate: £400-£600 (Outside IR35, Negotiable)
Contract Length: 6 months (with possible extension)
Industry: Government-funded Non-Profit
Salt Recruitment is hiring an experienced Senior Python Engineer on behalf of a government-funded non-profit organisation working on an AI-driven platform. This is a hands-on development role focused on FastAPI microservices, AI/ML integrations, and cloud deployment.
We are looking for a strong back-end engineer with a proven track record in building scalable microservices, working with AI/NLP models, and deploying applications in a cloud-based environment (AWS/GCP).
Key Responsibilities:
- Develop, maintain, and optimise Python microservices using FastAPI.
- Integrate AI/ML models and NLP technologies into backend services.
- Build and optimise data pipelines for machine learning applications.
- Deploy and manage services in AWS/GCP, using Docker, Kubernetes, and Terraform.
- Ensure best practices in testing (Pytest), CI/CD (GitHub Actions), and observability (OpenTelemetry).
- Work closely with data scientists, DevOps engineers, and product managers in an Agile team.
Essential Skills and Experience:
- Proven experience in a similar Senior Python Engineer role.
- Strong proficiency in Python, including both object-oriented and functional programming.
- Expertise in FastAPI and its ecosystem (Pydantic, SQLAlchemy, Alembic).
- Experience with microservices architecture and serverless/lambda functions.
- Strong database skills, particularly PostgreSQL.
- Familiarity with common Python libraries (Pandas, NumPy, Jupyter Notebooks).
- Experience with Git, GitHub, Docker, and cloud deployments.
- Understanding of monitoring and observability using OpenTelemetry.
Desirable Skills:
- Cloud expertise in AWS (certifications preferred).
- Infrastructure as Code (Terraform, Kubernetes).
- Hands-on experience with AI/ML frameworks (Scikit-Learn, TensorFlow, Hugging Face, PyTorch).
- Familiarity with ML/Gen AI tools (LangChain, MLFlow, SageMaker, Bedrock, Weights & Biases).
- Experience with OAuth, JWT authentication mechanisms.
Why Apply?
- Work on a cutting-edge AI/ML project with real-world impact.
- Flexible hybrid working with a London-based office.
- Outside IR35 contract with a competitive day rate (£400-£600).
- Exposure to modern cloud and AI technologies.
Applicants are also welcome to apply directly by emailing their CV to .
*Rates depend on experience and client requirements
Senior Python Engineer - FastAPI, AI/ML & Cloud employer: 402985
Contact Detail:
402985 Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Python Engineer - FastAPI, AI/ML & Cloud
✨Tip Number 1
Make sure to showcase your hands-on experience with FastAPI and microservices in your discussions. Highlight specific projects where you've built scalable applications, as this will resonate well with the hiring team.
✨Tip Number 2
Familiarize yourself with the latest AI/ML frameworks mentioned in the job description, like TensorFlow and Scikit-Learn. Being able to discuss how you've integrated these technologies into backend services can set you apart.
✨Tip Number 3
Since the role involves cloud deployment, brush up on your AWS or GCP knowledge. Be prepared to talk about your experience with Docker, Kubernetes, and Terraform, as these are crucial for the position.
✨Tip Number 4
Engage with the Agile methodology and be ready to discuss how you've collaborated with cross-functional teams. Sharing examples of your teamwork with data scientists and DevOps engineers will demonstrate your fit for the role.
We think you need these skills to ace Senior Python Engineer - FastAPI, AI/ML & Cloud
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, FastAPI, and cloud deployments. Include specific projects where you've built scalable microservices or integrated AI/ML models.
Craft a Strong Cover Letter: In your cover letter, express your passion for AI/ML and how your skills align with the job requirements. Mention your familiarity with tools like Docker, Kubernetes, and Terraform, and how you can contribute to the team.
Showcase Relevant Projects: If you have worked on relevant projects, describe them briefly in your application. Highlight your role, the technologies used, and the impact of the project, especially in relation to AI/ML and cloud environments.
Highlight Collaboration Skills: Since the role involves working closely with data scientists and DevOps engineers, emphasize your experience in Agile teams and your ability to collaborate effectively across different functions.
How to prepare for a job interview at 402985
✨Showcase Your Python Expertise
Be prepared to discuss your experience with Python in detail, especially focusing on object-oriented and functional programming. Highlight specific projects where you've utilized FastAPI and its ecosystem, as this will demonstrate your hands-on experience.
✨Demonstrate Your Cloud Knowledge
Since the role involves cloud deployment, make sure to talk about your experience with AWS or GCP. Discuss any relevant certifications you may have and be ready to explain how you've used Docker, Kubernetes, and Terraform in past projects.
✨Discuss AI/ML Integrations
Prepare to share examples of how you've integrated AI/ML models into backend services. Familiarize yourself with the frameworks mentioned in the job description, such as Scikit-Learn and TensorFlow, and be ready to discuss your approach to building data pipelines.
✨Emphasize Collaboration Skills
This role requires working closely with data scientists and DevOps engineers. Be ready to discuss your experience in Agile teams and how you’ve collaborated with cross-functional teams to deliver successful projects.
