Machine Learning Engineer
Posted 4 days ago by Ampstek
Negotiable
Undetermined
Undetermined
London Area, United Kingdom
Summary: The Lead Software Engineer (AI/ML/Python) will spearhead the design and development of advanced AI solutions, utilizing Python and various AI technologies. The role requires a strong focus on implementing scalable architectures and optimizing AI applications, particularly in the areas of machine learning and computer vision. The ideal candidate will possess hands-on experience in ML engineering and a passion for solving complex AI challenges. Collaboration with cross-functional teams and mentorship of junior members are also key aspects of this position.
Key Responsibilities:
- Lead the design, development, and deployment of AI/ML solutions using Python, LLMs, and agentic libraries (e.g., LangChain, LangGraph, AutoGen).
- Implement and optimize Retrieval-Augmented Generation (RAG) architecture for enterprise-grade AI applications.
- Develop efficient and secure pipelines for document processing and computer vision use cases.
- Engineer effective and scalable prompt templates and evaluation strategies for LLM-based systems.
- Manage and scale vector databases for storing and querying embeddings.
- Collaborate closely with cross-functional teams including data scientists, ML engineers, and DevOps to ensure seamless AI model integration.
- Evaluate and select appropriate ML frameworks, libraries, and tools to accelerate product development.
- Provide mentorship and technical leadership to junior team members.
Key Skills:
- Strong proficiency in Python and modern AI/ML libraries (e.g., PyTorch, TensorFlow, Transformers).
- Experience with LLMs (OpenAI, Claude, Mistral, LLaMA, etc.) and prompt engineering best practices.
- Practical experience with RAG architecture and building hybrid search/retrieval pipelines.
- Hands-on experience with vector databases (e.g., FAISS, Pinecone, Weaviate, Chroma).
- Familiarity with LangChain, LangGraph, or AutoGen for building agent-based AI applications.
- Background in computer vision (OpenCV, YOLO, OCR frameworks) and document data extraction.
- Solid understanding of MLOps, CI/CD for ML workflows, and cloud platforms (AWS/GCP/Azure).
- Proven leadership in delivering AI projects from concept to production.
Salary (Rate): undetermined
City: London Area
Country: United Kingdom
Working Arrangements: undetermined
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
Job Description – Roles & Responsibilities
We are seeking a Lead Software Engineer (AI/ML/Python) to join our innovative team focused on building intelligent, scalable AI solutions. You will lead the design and development of advanced systems leveraging Python, large language models (LLMs), vector databases, and cutting-edge architectures like RAG and agentic frameworks. The ideal candidate should have a passion for solving complex AI problems with hands-on experience in ML engineering, prompt engineering, and computer vision.
Key Responsibilities:
- Lead the design, development, and deployment of AI/ML solutions using Python , LLMs , and agentic libraries (e.g., LangChain, LangGraph, AutoGen).
- Implement and optimize Retrieval-Augmented Generation (RAG) architecture for enterprise-grade AI applications.
- Develop efficient and secure pipelines for document processing and computer vision use cases.
- Engineer effective and scalable prompt templates and evaluation strategies for LLM-based systems.
- Manage and scale vector databases for storing and querying embeddings.
- Collaborate closely with cross-functional teams including data scientists, ML engineers, and DevOps to ensure seamless AI model integration.
- Evaluate and select appropriate ML frameworks, libraries, and tools to accelerate product development.
- Provide mentorship and technical leadership to junior team members.
Required Skills & Experience:
- Strong proficiency in Python and modern AI/ML libraries (e.g., PyTorch, TensorFlow, Transformers).
- Experience with LLMs (OpenAI, Claude, Mistral, LLaMA, etc.) and prompt engineering best practices.
- Practical experience with RAG architecture and building hybrid search/retrieval pipelines.
- Hands-on experience with vector databases (e.g., FAISS, Pinecone, Weaviate, Chroma).
- Familiarity with LangChain, LangGraph, or AutoGen for building agent-based AI applications.
- Background in computer vision (OpenCV, YOLO, OCR frameworks) and document data extraction .
- Solid understanding of MLOps, CI/CD for ML workflows, and cloud platforms (AWS/GCP/Azure).
- Proven leadership in delivering AI projects from concept to production.