We’re looking for a Machine Learning Engineer to join a fast-growing global product team, working on cutting-edge Generative AI and scalable ML systems. If you’re passionate about building impactful AI solutions and working with modern ML infrastructure, this role is for you.

What You’ll Do:

• Design and develop robust, production-ready ML architectures with end-to-end ownership — from data pipelines to real-time inference.

• Build and fine-tune models using LLMs, RAG (Retrieval-Augmented Generation), and other GenAI techniques.

• Work with vector databases like FAISS, Pinecone, or Weaviate to build intelligent retrieval systems.

• Deploy models using cloud-native tools (AWS preferably), Docker, Kubernetes, and MLOps best practices.

• Collaborate closely with product, backend, and data teams to align solutions with real-world user needs.

• Mentor junior engineers and contribute to scaling the team’s technical capabilities.

What We’re Looking For:

• 8–12 years of experience in machine learning engineering or related software roles.

• Strong expertise in Python with deep knowledge of TensorFlow and PyTorch.

• Proven experience in LLMs, RAG systems, and Generative AI frameworks (e.g., LangChain).

• Hands-on knowledge of vector search, MLOps pipelines, and model monitoring/tuning.

• Experience deploying ML solutions in cloud environments (AWS preferred)

• Solid grasp of data structures, algorithms, and distributed systems.

If this role is in line with your profile, write to me at [email protected] and let's connect!