Machine Learning Engineer – AI Production Services

About the role

We are expanding our AI engineering team and seeking a Machine Learning Engineer to develop production AI features for a SaaS platform. The role involves building APIs, workers, pipelines, and intelligent recommendation systems using Python.

Key responsibilities

• Build production AI/ML services in Python, including APIs, workers, async pipelines, storage integrations, and service workflows.
• Apply classical machine‑learning, statistics and evaluation methods to ranking, recommendation, personalization and output‑quality measurement.
• Model product feedback loops using reinforcement‑learning concepts such as states, actions, rewards and policies.
• Develop intelligent navigation and recommendation systems from user interaction signals.
• Work with deep‑learning and open‑source models, including embeddings, rerankers, classifiers and fine‑tuned models.
• Design and implement agentic workflows for document generation, template editing, memory retrieval and multi‑step execution.
• Ensure code quality through testing, logging, maintainability and deployment readiness, and contribute to a secure multi‑tenant AI/ML architecture.

Required profile

• 1–3 years of experience in backend, software, data, ML or AI engineering.
• Strong hands‑on Python development with solid software‑engineering habits.
• Experience building backend services, APIs, workers or production data/ML pipelines.
• Familiarity with databases, queues, object storage, Docker, async processing and basic cloud infrastructure (preferably Azure).
• Solid understanding of classical ML techniques, probability, statistics, linear algebra and optimization.
• Knowledge of reinforcement‑learning fundamentals.

Required skills

• Python
• Pandas, NumPy, scikit‑learn
• Azure (or similar cloud platform)
• Docker
• APIs, databases, message queues, object storage
• Async processing
• Reinforcement learning concepts
• Deep‑learning frameworks and open‑source models (embeddings, LLMs)