Python Backend Developer / ML Engineer

Join a forward-thinking company revolutionizing business operations with an advanced AI-powered platform. This platform leverages cutting-edge analytics and machine learning to process vast datasets, delivering actionable insights and predictive capabilities across diverse industries, including healthcare. It is designed for seamless integration, empowering teams to make rapid, data-driven decisions and drive innovation.

About the Role

We are seeking a skilled Python Backend Developer with a strong Machine Learning focus to contribute to the development of our client's innovative AI platform. You will play a key role in building scalable backend systems, designing APIs, and implementing advanced machine learning models, particularly focusing on production LLM systems.

Key Responsibilities

• Design and develop robust, scalable backend systems and APIs using Python and FastAPI, adhering to SOLID principles and asynchronous patterns.
• Write high-quality, maintainable Python code, incorporating features like async/await, type hints, and Pydantic.
• Implement and manage production LLM systems, including transformers, prompt engineering, embeddings, and vector search.
• Integrate with vector databases (e.g., Pinecone, Weaviate, Chroma) and develop hybrid search functionalities.
• Apply MLOps best practices, utilizing tools like MLflow for model versioning and A/B testing. Experience with Langfuse is preferred.
• Develop solutions for NLP and computer vision tasks, such as document understanding, OCR, and integrating with models like GPT-4 Vision.
• Build and optimize feature pipelines, real-time and batch inference systems, and model serving infrastructure.
• Leverage HuggingFace for machine learning tasks, with familiarity in LangChain/LlamaIndex being a plus.
• Utilize Azure OpenAI (GPT-4, GPT-4 Vision) with robust error handling and retry mechanisms.
• Implement LLM observability using Langfuse to track prompts, tokens, costs, and latency.
• Develop sophisticated prompt management strategies, including versioning, fallbacks, and cost optimization.
• Orchestrate complex asynchronous workflows using Celery.
• Design and implement multi-tenant architectures with a strong emphasis on data isolation and security.
• Integrate with various third-party APIs, including Veeva Vault and Adobe PDF Services.
• Troubleshoot and debug systems using structured logging and distributed tracing.
• Document APIs and system changes comprehensively using OpenAPI/Swagger specifications.

Requirements

• Bachelor’s or Master’s degree in Computer Science or a related field.
• A minimum of 4 years of hands-on experience in Machine Learning and production LLM systems.
• Solid understanding of ML fundamentals, including transformers, prompt engineering, embeddings, and vector search.
• Proven experience with backend API development using FastAPI, async patterns, and rate limiting.
• Hands-on experience with vector databases (Pinecone, Weaviate, Chroma) and hybrid search.
• Advanced proficiency in Python, including async/await, type hints, Pydantic, and SOLID principles.
• Experience in MLOps, including MLflow, model versioning, and A/B testing.
• Familiarity with NLP and computer vision concepts and tools (e.g., document understanding, OCR, GPT-4 Vision).
• Experience in building feature pipelines, inference systems, and model serving.
• Mandatory familiarity with HuggingFace.

Nice to Have Skills

• Understanding of DevOps practices, including CI/CD pipelines (Azure DevOps, GitHub Actions), Docker, and Kubernetes.
• Knowledge of data security best practices, including multi-tenant data isolation and secure key management (Azure Key Vault).
• Experience designing solutions on cloud platforms, with a strong preference for Azure (Azure OpenAI, Blob Storage, Key Vault, Container Registry). Experience with AWS or GCP is also valuable.
• Experience in data engineering with Big Data systems, including large-scale data processing and ETL/ELT pipelines.

Benefits

• Engage in impactful and exciting projects.
• Access Udemy courses for continuous learning.
• Participate in team-building events, workshops, and training sessions.
• Benefit from a clear career progression path.
• Enjoy ample absence days for work-life balance.
• Experience flexible working hours and the freedom to work from anywhere.