Machine Learning Platform Engineer, Machine Learning, Artificial Intelligence

This is a fully remote position, open to applicants in Mali, +1 more country.

📋 Description

• Develop and maintain the Machine Learning (ML) infrastructure and platforms that drive Artificial Intelligence (AI) products.

• Create systems for model training, evaluation, deployment, inference, and experimentation.

• Construct and enhance model serving and inference infrastructure to accommodate high-throughput and low-latency demands.

• Enhance the reliability, scalability, latency, and cost-effectiveness of Artificial Intelligence (AI) systems.

• Design dependable pipelines for data preparation, training, evaluation, model deployment, and ongoing enhancement.

• Create platforms and tools that empower Artificial Intelligence (AI) engineers and researchers to experiment, assess, and deploy models more efficiently.

• Develop infrastructure for evaluation and benchmarking to assess model quality, performance, and potential regressions.

• Implement production-level observability, monitoring, tracing, and alerting for Artificial Intelligence (AI)/Machine Learning (ML) applications.

• Identify performance bottlenecks within the Machine Learning (ML) stack and consistently enhance system efficiency.

• Collaborate closely with Artificial Intelligence (AI) engineers, researchers, and product teams to translate evolving model requirements into production-ready infrastructure.

• Ensure that AI infrastructure consistently supports production workloads at scale.

• Guarantee that models can be trained, assessed, deployed, and improved in an efficient manner.

• Ensure that inference systems provide excellent latency, throughput, reliability, and cost efficiency.

• Maintain that Machine Learning (ML) pipelines are reproducible, observable, maintainable, and robust.

• Swiftly detect and diagnose regressions in models and infrastructure.

• Create reusable primitives for the Machine Learning (ML) infrastructure platform.

• Facilitate the rapid evolution of the AI stack as new models, architectures, and inference techniques are developed.

⛳️ Requirements

• Proven experience in Machine Learning (ML) and Artificial Intelligence (AI).

• Solid foundation in software engineering principles and experience in building production systems.

• Experience in constructing Machine Learning (ML) infrastructure, platforms, or operational machine learning systems.

• Familiarity with model deployment, inference, evaluation, or data pipelines.

• Strong grasp of distributed systems and system reliability.

• Capability to write clean, maintainable, production-quality code.

• Comfortable navigating ambiguous and fast-paced environments.

• A proactive approach towards ownership, experimentation, and continuous improvement.

• Proficiency in Python, PyTorch, JAX, LLM, and ML serving infrastructures such as vLLM, SGLang, or TensorRT-LLM, along with cloud infrastructure, distributed systems, ML/data pipelines, workflow orchestration, GPU infrastructure and performance tools, and vector databases and retrieval systems.

• Willingness to complete a 60-minute coding assessment.

🏝️ Benefits

• Medical insurance.

• Dental insurance.

• Vision insurance.

• Savings Plan Options.

• Paid Time Off (PTO).