Senior Machine Learning Engineer - AI Platforms
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About the role
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Senior Machine Learning Engineer (Remote – Lagos, NG)
Location: Fully remote (based out of Lagos, Nigeria)
Team: AI & Data Science – Global, fully distributed
Employment type: Full‑time, permanent
About Us
We are a fast‑growing AI‑first company that builds cutting‑edge machine‑learning platforms powering the next generation of products across multiple industries. Our mission is to turn complex data into intelligent, scalable solutions that drive real‑world impact. Join a passionate, high‑performing team that values innovation, autonomy, and continuous learning.
Why You’ll Love This Role
- Impact: Design and ship AI models that directly influence product strategy and revenue.
- Autonomy: Work remotely with a flexible schedule while collaborating with top talent worldwide.
- Growth: Stay at the forefront of research, experiment with the latest frameworks, and mentor the next generation of engineers.
- Tech Stack: Python, TensorFlow/PyTorch, Scikit‑learn, Spark, Kubernetes, Terraform, AWS/GCP/Azure, MLflow, Docker, and more.
Key Responsibilities
- Model Development: Design, implement, and optimize scalable ML/DL models and algorithms for production use.
- Platform Engineering: Build and maintain robust AI infrastructure (data pipelines, feature stores, model registries, CI/CD for ML).
- End‑to‑End Workflow: Own the full lifecycle—from data ingestion & feature engineering to training, evaluation, and deployment.
- MLOps: Deploy models using best‑in‑class MLOps practices (containerization, orchestration, monitoring, automated rollback).
- Collaboration: Partner with data scientists, software engineers, and product managers to translate business needs into technical solutions.
- Performance Tuning: Continuously profile, benchmark, and improve model latency, throughput, and resource utilization.
- Thought Leadership: Keep abreast of the latest AI research, propose innovative approaches, and contribute to architectural decisions.
- Mentorship: Guide junior engineers, conduct code reviews, and foster a culture of knowledge sharing.
- Troubleshooting: Diagnose and resolve production issues across data pipelines, model serving, and monitoring systems.
Required Qualifications
| Requirement | Details |
|---|---|
| Education | Master’s or Ph.D. in Computer Science, AI, Machine Learning, Statistics, or a related quantitative field. |
| Experience | 5+ years in machine‑learning engineering or a closely related role. |
| Programming | Expert‑level Python; strong command of ML libraries (TensorFlow, PyTorch, Scikit‑learn). |
| Cloud & MLOps | Hands‑on experience with AWS, Azure, or GCP; familiar with CI/CD tools (GitHub Actions, Jenkins), container orchestration (Kubernetes), and MLOps platforms (MLflow, Kubeflow, Seldon, etc.). |
| Big Data | Proficient with Spark, Hadoop, or similar distributed processing frameworks. |
| Software Engineering | Solid understanding of data structures, algorithms, design patterns, and version control (Git). |
| Analytical Skills | Proven ability to translate ambiguous business problems into data‑driven solutions. |
| Communication | Excellent written and verbal communication; comfortable presenting technical concepts to non‑technical stakeholders. |
| Remote Work | Demonstrated success working independently in a distributed team environment. |
Preferred (but not required)
- Publications or contributions to open‑source ML projects.
- Experience with reinforcement learning, graph neural networks, or large language models.
- Knowledge of data governance, privacy, and security best practices.
What We Offer
- Competitive salary + performance‑based bonuses.
- Comprehensive health insurance (local and international options).
- Professional development stipend (conferences, courses, certifications).
- Flexible working hours and a fully remote setup.
- Collaborative culture with regular virtual hackathons, tech talks, and mentorship programs.
How to Apply
Send your résumé, a brief cover letter highlighting a recent ML project you’re proud of, and links to any relevant GitHub repositories or publications to hr@yourcompany.com with the subject line “Senior ML Engineer – Lagos”.
We look forward to building the future of AI together!
Feel free to adjust any section (benefits, tech stack, company name, etc.) to better match your brand voice or specific requirements.
Requirements
- Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- 5+ years of experience in machine learning engineering or a related role.
- Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
- Experience with cloud platforms (AWS, Azure, GCP) and MLOps tools.
- Strong understanding of data structures, algorithms, and software engineering principles.
- Experience with big data technologies (e.g., Spark, Hadoop).
- Excellent problem-solving and analytical skills.
- Strong communication and collaboration skills.
- Proven ability to work independently and manage multiple projects in a remote setting.
Responsibilities
- Design, develop, and implement scalable machine learning models and algorithms.
- Build and maintain robust AI platforms and infrastructure.
- Perform data analysis, feature engineering, and model training/evaluation.
- Deploy machine learning models into production environments using MLOps best practices.
- Collaborate with cross-functional teams to define project requirements and deliverables.
- Optimize model performance and ensure scalability and reliability.
- Stay current with advancements in AI, machine learning, and deep learning research.
- Mentor and guide junior machine learning engineers.
- Contribute to architectural discussions and technical strategy.
- Troubleshoot and resolve issues related to ML systems and pipelines.
Skills
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