Machine Learning Engineer

About:

We’re looking for a passionate Machine Learning Engineer to join our team and dive into the exciting world of Generative AI. You’ll work on cutting-edge demos and proof of concepts (POCs), turning bold ideas into reality. The ideal candidate brings solid Back-end engineering skills and a curiosity for Generative AI development. If you’re familiar with MLOps, large language models (LLMs), or concepts like Retrieval-Augmented Generation (RAG). Experience in the Banking and Financial Services domain will be a significant advantage.

You will be exposed to a variety of tasks, including:

● Develop Proof of Concepts (PoC). Test and validate new ideas

● Drive implementation, optimizing and transforming data solutions to improve business outcomes

● Help with offerings as a technical consultant

Requirements:

● 4+ years of experience in IT 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 in pre-sales 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 basics (security, governance, etc.)

● Experience with cloud platforms (AWS, Google Cloud, Azure) or on-premises setups

● Strong problem-solving skills and ability to handle shifting priorities with Support team

● Experience with client-facing roles

● Excellent presentation and demonstration skills

● 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:

● Contributions to open-source projects or experience with tools like Airflow or Spark

● Familiarity with containers (e.g., Docker) or orchestration tools (e.g., Kubernetes)

● Experience in the Banking and Financial Services domain

● Exposure to prompt engineering or fine-tuning LLMs

● Knowledge of other languages like Java or Go

Responsibilities:

● 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 guidance to ensure Generative AI applications are secure and meetbasic 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 requirements

● 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