Senior AI​/ML Engineer - Distributed Systems

About the Role Our client is a fast-growing technology firm seeking a highly experienced Senior AI/ML Engineer with expertise in Distributed Systems to join their fully remote team. This role is critical for building and scaling the AI infrastructure that powers our client's innovative products. You will focus on designing, implementing, and maintaining robust, high-performance distributed systems for machine learning model training, inference, and data processing.

The ideal candidate will possess a deep understanding of distributed computing principles, cloud infrastructure, and large-scale ML operations (MLOps). This is a remote-first position, offering flexibility and the opportunity to work with a globally distributed team of talented engineers and researchers. Our client is committed to fostering a culture of innovation, collaboration, and continuous learning, providing the resources and support needed to tackle complex technical challenges.

You will play a key role in architecting solutions that ensure our AI systems are scalable, reliable, and efficient, contributing significantly to the company's technological advancements. Be part of a team that values autonomy, excellence, and the pursuit of cutting‑edge solutions.

• Design, develop, and implement scalable and reliable distributed systems for AI and machine learning workloads.
• Optimize ML training and inference pipelines for performance and efficiency using distributed computing techniques.
• Manage and monitor large-scale ML infrastructure on cloud platforms (e.g., AWS, Azure, GCP).
• Implement and advocate for MLOps best practices, including CI/CD, automated testing, and deployment strategies.
• Develop tools and frameworks to streamline the ML development lifecycle.
• Collaborate with data scientists and ML researchers to understand their infrastructure needs and provide solutions.
• Troubleshoot and resolve complex issues in distributed AI systems.
• Contribute to architectural decisions and technology selection for the AI platform.
• Ensure the security, scalability, and cost-effectiveness of the distributed infrastructure.

• Master's or PhD in Computer Science, Software Engineering, or a related field.
• Proven experience building and managing large-scale distributed systems.
• Strong understanding of cloud computing platforms (AWS, Azure, or GCP) and their services.
• Proficiency in programming languages like Python, Go, or Java.
• Experience with containerization technologies (Docker, Kubernetes).
• Familiarity with distributed data processing frameworks (e.g., Spark, Dask).
• Knowledge of machine learning concepts and workflows.
• Experience with MLOps tools and practices is highly desirable.
• Excellent problem-solving and debugging skills.
• Strong communication skills for effective remote collaboration.

• Competitive salary and performance-based bonuses.
• Comprehensive health, dental, and vision insurance plans.
• Generous home office setup budget.
• Flexible working hours and a fully remote work environment.
• Opportunities for professional development and continuous learning.
• Access to cutting-edge technologies and challenging projects.
• Collaborative and supportive team culture.
• Work with a global team on impactful AI initiatives.