Machine Learning Engineer

3 weeks ago

WorkFromHome, South Africa Dijkstrack Ltd Full time

This 12-month remote contract role places you on an international machine learning project through Dijkstrack for one of our global technology partners. You’ll work within a distributed engineering team to design, train, and deploy ML models using modern frameworks like PyTorch. Dijkstrack engineers enjoy access to technical community support, structured delivery processes, and the opportunity to embed within long-term global product teams. Key Duties & Responsibilities Design, train, and deploy machine learning and deep learning models using PyTorch. Build and maintain ML pipelines, model training workflows, and data processing components. Work with product and engineering teams to integrate models into production systems. Analyse datasets, performance metrics, and optimise models for accuracy and efficiency. Implement MLOps best practices for model versioning, deployment, and monitoring. Document models, datasets, evaluations, and maintain reproducibility standards. Participate in code reviews and uphold engineering quality in ML codebases. Essential Skills & Technical Requirements Strong proficiency in Python for ML development. Hands‑on experience with PyTorch (TensorFlow experience also welcome). Solid understanding of machine learning fundamentals, model architectures, training loops. Ability to work with large datasets, ETL pipelines, and model optimisation. Familiarity with Git workflows, remote collaboration, and agile delivery models. Beneficial / Nice‑to‑Have Experience Experience with MLOps tools like MLflow, Weights & Biases, SageMaker, or similar. Exposure to cloud‑based ML deployments (AWS, Azure, GCP). Knowledge of microservice integration for ML models. Prior work in AI product teams or international ML research environments. Benefits of Working with Dijkstrack Join a network of engineers delivering advanced ML solutions internationally. Technical community of senior engineers across data, backend, and product domains. Remote‑first culture, global exposure, and structured technical delivery support. #J-18808-Ljbffr

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