Job Description
As a Python Data Expert at SS&C, you will play a key role in the Data Platform, shaping hedge fund administration technology, streamlining daily workflows, and enhancing reporting for fund accountants, investment managers, clients, and investors. You’ll be part of a dedicated and passionate team driven by intellectual curiosity, problem-solving, and a commitment to delivering impactful solutions. We seek capable leaders eager to learn new technologies, embrace best practices, and foster a collaborative, fun work environment.
Join us to grow and learn while practising continuous integration and delivery, leveraging the agile methodology, and building high-quality, valuable features using a test-driven approach.
Key Responsibilities:
Lead the development of robust, high-performance web and generative AI applications.
Build and deploy GenAI solutions leveraging Retrieval-Augmented Generation (RAG) pipelines for intelligent document querying, summarisation, and semantic search.
Extract, structure, and process data from complex documents (PDFs, images, scanned forms) using integrated OCR engines (e.g., Tesseract, PaddleOCR) and vision-language models.
Develop RAG-based GenAI applications using tools like LangChain and LlamaIndex, and work with vector databases (e.g., FAISS, Weaviate) for efficient embedding-based retrieval.
Integrate OCR, LLMs, and vector search into business applications to automate the extraction, understanding, and processing of unstructured content.
Design, train, and optimise both Small Language Models (SLMs) and Large Language Models (LLMs) for domain-specific applications, ensuring efficiency and high performance.
Develop scalable training pipelines leveraging methods such as supervised fine-tuning, reinforcement learning from human feedback (RLHF), prompt tuning, parameter-efficient fine-tuning (e.g., LoRA, adapters), and knowledge distillation.
Fine-tune, evaluate, and deploy language models using advanced techniques like quantisation, continual learning, and model distillation to meet evolving business requirements.
Analyse and monitor model outputs for quality, bias, and safety, iterating to improve accuracy and model alignment with user and business needs.
Architect, design, and implement scalable and secure solutions aligned with business objectives.
Mentor and guide a team of developers, fostering a culture of continuous learning and improvement.
Design and maintain APIs, including RESTful and GraphQL interfaces, ensuring seamless data exchange with third-party services.
Implement and maintain CI/CD pipelines, utilising automation tools for seamless deployment.
Collaborate with cross-functional teams, including DevOps, Security, Data Science, and Product Management.
Optimise application performance by efficiently managing resources, implementing load balancing, and optimising queries.
Ensure compliance with industry security standards such as GDPR.
Stay updated with emerging technologies, especially in Generative AI, Machine Learning, cloud computing, and microservices architecture.
Required Qualifications:
Bachelor’s or master’s degree in computer science, Engineering, or a related field.
6+ years of hands-on experience in AI & Python development, with expertise in Django, Flask, or FastAPI.
Ability to design and build end-to-end applications and API integrations.
Proven experience with large language models (LLMs) and AI model development
Experience with developing retrieval-augmented generation (RAG).
Experience with GenAI tools like Langchain, LlamaIndex, LangGraph, and open-source Vector DBs.
Exposure to prompt engineering principles and techniques like chain of thought, in-context learning, tree of thought, etc.
Exposure to SLMs.
Experience with supervised fine-tuning, reinforcement learning from human feedback (RLHF), prompt tuning, parameter-efficient fine-tuning (e.g., LoRA, adapters), and knowledge distillation.
Experience with relational databases such as MS SQL Server, PostgreSQL, and MySQL.
Expertise in DevOps practices, including Docker, Kubernetes, and CI/CD tools like GitHub Actions.
Deep understanding of microservices architecture and distributed computing principles.
Strong knowledge of security best practices in software development.
Familiarity with data analytics and visualisation tools such as Snowflake, Looker, Tableau, or Power BI.
Excellent problem-solving skills and the ability to work independently and within a team.
Strong communication and stakeholder management skills.
Join us to grow and learn while practising continuous integration and delivery, leveraging the agile methodology, and building high-quality, valuable features using a test-driven approach.
Key Responsibilities:
Lead the development of robust, high-performance web and generative AI applications.
Build and deploy GenAI solutions leveraging Retrieval-Augmented Generation (RAG) pipelines for intelligent document querying, summarisation, and semantic search.
Extract, structure, and process data from complex documents (PDFs, images, scanned forms) using integrated OCR engines (e.g., Tesseract, PaddleOCR) and vision-language models.
Develop RAG-based GenAI applications using tools like LangChain and LlamaIndex, and work with vector databases (e.g., FAISS, Weaviate) for efficient embedding-based retrieval.
Integrate OCR, LLMs, and vector search into business applications to automate the extraction, understanding, and processing of unstructured content.
Design, train, and optimise both Small Language Models (SLMs) and Large Language Models (LLMs) for domain-specific applications, ensuring efficiency and high performance.
Develop scalable training pipelines leveraging methods such as supervised fine-tuning, reinforcement learning from human feedback (RLHF), prompt tuning, parameter-efficient fine-tuning (e.g., LoRA, adapters), and knowledge distillation.
Fine-tune, evaluate, and deploy language models using advanced techniques like quantisation, continual learning, and model distillation to meet evolving business requirements.
Analyse and monitor model outputs for quality, bias, and safety, iterating to improve accuracy and model alignment with user and business needs.
Architect, design, and implement scalable and secure solutions aligned with business objectives.
Mentor and guide a team of developers, fostering a culture of continuous learning and improvement.
Design and maintain APIs, including RESTful and GraphQL interfaces, ensuring seamless data exchange with third-party services.
Implement and maintain CI/CD pipelines, utilising automation tools for seamless deployment.
Collaborate with cross-functional teams, including DevOps, Security, Data Science, and Product Management.
Optimise application performance by efficiently managing resources, implementing load balancing, and optimising queries.
Ensure compliance with industry security standards such as GDPR.
Stay updated with emerging technologies, especially in Generative AI, Machine Learning, cloud computing, and microservices architecture.
Required Qualifications:
Bachelor’s or master’s degree in computer science, Engineering, or a related field.
6+ years of hands-on experience in AI & Python development, with expertise in Django, Flask, or FastAPI.
Ability to design and build end-to-end applications and API integrations.
Proven experience with large language models (LLMs) and AI model development
Experience with developing retrieval-augmented generation (RAG).
Experience with GenAI tools like Langchain, LlamaIndex, LangGraph, and open-source Vector DBs.
Exposure to prompt engineering principles and techniques like chain of thought, in-context learning, tree of thought, etc.
Exposure to SLMs.
Experience with supervised fine-tuning, reinforcement learning from human feedback (RLHF), prompt tuning, parameter-efficient fine-tuning (e.g., LoRA, adapters), and knowledge distillation.
Experience with relational databases such as MS SQL Server, PostgreSQL, and MySQL.
Expertise in DevOps practices, including Docker, Kubernetes, and CI/CD tools like GitHub Actions.
Deep understanding of microservices architecture and distributed computing principles.
Strong knowledge of security best practices in software development.
Familiarity with data analytics and visualisation tools such as Snowflake, Looker, Tableau, or Power BI.
Excellent problem-solving skills and the ability to work independently and within a team.
Strong communication and stakeholder management skills.
💡 Quick Summary
Seeking a career-building opportunity? The Python, Data Engineer position is now open for candidates interested in the IT Engineer & Developer Jobs sector. This role in London offers a professional environment and growth potential.
Requirement Snapshot: Candidates should possess basic communication skills, a proactive attitude, and the ability to work in a team. Experience in IT Engineer & Developer Jobs is a plus.
