Machine Learning Engineer (Financial Services domain)

Join our team as a Machine Learning Engineer, shaping the future of Generative AI with cutting-edge demos, scalable architectures, and hands-on development.

We’re looking for a passionate Machine Learning Engineer to join our team and dive into the exciting world of Generative AI. You’ll get hands-on experience with cutting-edge demos and proof of concepts (POCs), turning bold ideas into reality. The ideal candidate has solid Back-end engineering skills and is curious about Generative AI development. If you’re familiar with MLOps, large language models (LLMs), or concepts like Retrieval-Augmented Generation (RAG) is a plus, as is experience with Front-end languages! Experience in the Financial Services domain, particularly Banking, will be a big plus.

You will be exposed to a variety of tasks, including: Develop proof of concepts (PoC). Test and validate new ideas Drive implementation. Optimize and transform data solutions to improve business outcomes Help with proposals as a technical consultant.

Job Description Assist in building and testing Generative AI demos and POCs Support the design of simple, scalable architectures for Generative AI applications Work with team members to integrate AI components into larger systems Use MLOps practices to help automate parts of the model development process Follow guidelines to ensure that Generative AI applications are secure and meet basic governance standards Help deploy AI applications on cloud platforms or on-premises setups with team support Adapt to a fast-paced environment with evolving project needs Keep up with AI trends and apply them to projects with guidance Advise clients. Understand their needs, analyze possible solutions, and present the best options

Qualifications 4+ years of experience in IT industry, with at least 2-3 years of experience in machine learning Solid Back-end engineering skills, particularly with Python (e.g., Django, Flask, or FastAPI). Experience with pre-sales activities and opportunity processing Basic experience with databases or tools like vector databases (e.g., Pinecone, Weaviate, Faiss) Familiarity with AI frameworks such as TensorFlow, PyTorch, or Hugging Face Understanding of CI/CD pipelines Knowledge of RAG or AI application fundamentals (security, governance, etc.) Experience with cloud platforms (AWS, Google Cloud, Azure) or on-premises setups Ability to solve problems and handle shifting priorities with team support Experience with client-facing roles Ability to demonstrate ideas and solutions clearly and confidently Bachelor's or Master's degree in computer science, machine learning, artificial intelligence, or a related field Upper-Intermediate level of English

Would be a plus Knowledge of other programming languages, such as Java or Go Experience with open-source projects or exposure to tools, such as Airflow or Spark Familiarity with containers (e.g., Docker) or orchestration tools (e.g., Kubernetes) Experience in the Banking and Financial Services domain Experience with prompt engineering or fine-tuning LLMs