Machine Learning Specialist

Talent Safari
Nairobi
Workplace: HybridFull timeFunction: Data Science & Machine LearningExperience: 7+ yearsSkills: ["Model governance","Quality assurance","Mentoring","Communication","Self-directed problem-solving"]

Own the end-to-end machine learning lifecycle for production models, including training, validation, deployment, and continuous monitoring. Build reproducible MLOps pipelines on AWS with version control, model registry, and experiment tracking. Establish governance with auditable validation protocols (internal holdouts vs independent field validation), manage multi-crop and cross-country generalization, and oversee ground-truth data strategies. Lead a small team and communicate model methodology to institutional partners.

Loading

Loading job details...

Preparing the role view and application actions.

FursaFursa
Talent Safari
Talent Safari
1 day ago

Machine Learning Specialist

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 8 hours agoStatus: Live

Job Summary

Own the end-to-end machine learning lifecycle for production models, including training, validation, deployment, and continuous monitoring. Build reproducible MLOps pipelines on AWS with version control, model registry, and experiment tracking. Establish governance with auditable validation protocols (internal holdouts vs independent field validation), manage multi-crop and cross-country generalization, and oversee ground-truth data strategies. Lead a small team and communicate model methodology to institutional partners.
Location: Nairobi
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Own the complete ML lifecycle for all production models, including development, validation, deployment, and ongoing performance monitoring.
  • •Architect and maintain reproducible ML pipelines on AWS with version control, documentation, and independent reproducibility.
  • •Enforce model validation and sign-off protocols, including internal holdouts vs independent field validation, and run quarterly governance reviews.
  • •Design and oversee ground-truth data collection strategies using field surveys, drone imagery, crop-cut samples, and in-person validation.
  • •Mentor and lead junior data science team members and collaborate with product, engineering, and client-facing teams to deliver model insights to stakeholders.

Key Requirements

  • •7+ years of professional experience in machine learning with expertise in geospatial ML, remote sensing, or agricultural applications.
  • •Hands-on experience analyzing satellite imagery (e.g., Sentinel, Planet Labs), vegetation indices, and time-series modeling for crop/environment applications.
  • •Proven track record building ML governance and quality systems for environments where processes previously didn’t exist.
  • •Strong MLOps foundation including Git version control, model registry, experiment tracking, reproducible training pipelines, and deployment automation.
  • •Experience managing or mentoring small technical teams (2–5 people) and working with sparse, noisy, or incomplete datasets.
Experience:7+ yearsGeospatial MLRemote sensingAgriculturalMLOpsAWS
Skills:Model governanceQuality assuranceMentoringCommunicationSelf-directed problem-solving
Tech Stack:AWSS3EC2ECSIAMGitModel registryExperiment trackingSentinelPlanet LabsKoboToolboxProphetLSTMXGBoostCNNsSAM

Company Brief

Talent Safari
Talent Safari is a recruitment platform connecting employers with vetted tech and product talent through targeted hiring solutions, talent sourcing, and recruitment services to accelerate team growth and hiring outcomes.
Industry: Recruitment Agencies
Company Size: Small (11 to 50 employees)
Growth: Early Stage Startup
Website