Machine Learning Engineer (Financial Services domain)

• 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 

• 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