Lead MLOps Engineer – Privacy-First AI/ML Infrastructure

About the role

We are seeking a Lead MLOps Engineer to design and scale privacy-first AI/ML infrastructure for our global products. The role sits at the intersection of large-scale distributed systems and privacy engineering, ensuring that user privacy is built into every layer of the platform.

Key responsibilities

• Research and develop state-of-the-art AI/ML solutions and tooling that transform model training, deployment, and monitoring.
• Design secure, private, and high-performance systems, embedding privacy protections by design.
• Act as a technical leader, partnering with cross-functional teams, contributing to design discussions, and mentoring junior engineers.
• Drive engineering excellence through design reviews, rigorous code reviews, and robust test automation.

Required profile

• 5-7+ years of professional software engineering experience with a strong focus on AI/ML.
• Master’s or PhD in Machine Learning, Computer Science, Computer Engineering, or equivalent.
• Deep understanding of traditional ML, generative AI, and high-scale distributed data processing.
• Proven experience designing and scaling production ML infrastructure and mentoring engineers.

Required skills

• Python (primary language); working proficiency in Java and/or Scala.
• ML frameworks: PyTorch, TensorFlow, or JAX.
• Distributed computing: Ray, Apache Spark.
• Kubernetes and containerized infrastructure for ML workloads.
• ML pipeline tools such as MLflow.

What we offer

• Opportunity to work on bleeding-edge, privacy-focused AI projects.
• Highly motivated and dedicated team environment.
• Competitive salary and flexible schedule.
• Benefits package including medical insurance, sports, corporate social events, and professional development.
• Well-equipped office.