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MLOps Engineer with 7+ years in ML Infrastructure & Distributed Training
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Assessing your cultural and operational fit
Senior MLOps and ML Systems Engineer with 6+ years of experience architecting and optimizing production ML infrastructure. Deep expertise in PyTorch, JAX (explored), and custom GPU kernel development using Pallas and Triton, including tiling strategies, memory layout optimization, and kernel fusion. Proven track record in distributed training with FSDP, tensor parallelism, and pipeline parallelism for large-scale models. Skilled in designing evaluation frameworks, writing technical rubrics, and guiding research teams to close knowledge gaps in MLOps and ML systems engineering.
The African Institute for Mathematical Science
Master's in Machine Intelligence · Machine Intelligence
January 1, 2021 – May 1, 2022
Federal University of Technology, Akure, Nigeria
B. Tech. Physics (Electronics) · Physics (Electronics)
January 1, 2015 – December 1, 2019
BrassinAi
Research Engineer
August 1, 2025 – Present
India
Datopian
Senior Software Engineer
November 1, 2020 – December 1, 2025
India
Data Science Nigeria
Software / ML Engineer
February 1, 2020 – October 1, 2020
India
Demz Analytics
Software Engineer
October 1, 2019 – February 1, 2020
India
Microvm
June 1, 2025 – July 1, 2025
Implemented a Firecracker-based micro-VM runtime in Go to prototype edge-worker architecture for serverless ML inference, enabling scalable model serving with isolated execution environments. Gained experience in resource isolation and distributed scheduling applicable to GPU cluster management.
Go-ml Deployment
February 1, 2025 – June 1, 2026
Enhanced scikit-learn ONNX model performance by optimizing inference pipeline and designing a Go-based deployment service, reducing memory usage by 20% and improving throughput for production ML workloads. Currently exploring JAX model conversion and Triton kernel integration for further acceleration.
Postgres-redis
January 1, 2024 – April 1, 2024
Developed a PostgreSQL extension in Rust that synchronizes SQL query results with Redis, achieving sub-100ms cache lookups for real-time ML feature stores and data pipelines. Demonstrated low-level systems programming skills relevant to kernel-level optimization.
Machine Learning blog on Medium
Unknown
June 1, 2026 – Present
Systems blog on GitHub Pages
Unknown
June 1, 2026 – Present
Building Data-Driven Applications with Danfojs
Packt Publisher
September 1, 2021 – Present
Cultural Fit Analysis
The candidate's diverse project experience, including personal projects in Go-based ML deployment and micro-VM runtimes, indicates a proactive and innovative mindset. Their involvement in standardizing ML curriculum and presenting at conferences suggests a commitment to knowledge sharing and continuous learning. The breadth of skills and technologies used across different roles and projects demonstrates adaptability and a strong desire to explore new solutions, which is a good cultural fit for a dynamic MLOps environment.
Soft Skills & Operational Fit
The candidate demonstrates strong leadership in technical guidance, team collaboration, and curriculum development. Their experience in leading integration projects and providing technical feedback indicates good communication and problem-solving skills. The focus on optimizing performance and reliability aligns well with operational excellence.