867 Machine Learning Engineers jobs in Kenya

Company Description

At AgroNest Ventures Private Limited, we are transforming the future of agriculture with cutting-edge solutions that empower farmers, optimize resources, and promote sustainability. As a forward-thinking agri-tech company, we are committed to delivering technology-driven solutions across the agricultural value chain. We develop advanced agricultural technologies, promote eco-friendly practices, and empower farmers with data-driven insights and modern tools. Our vision is to be a global leader in sustainable agriculture, fostering prosperity through innovation and transforming how the world grows its food.

Role Description

This is a full-time hybrid role for a Machine Learning Engineer located in Nairobi County, Kenya, with some work-from-home flexibility. The Machine Learning Engineer will be responsible for developing and implementing machine learning algorithms and models, conducting research on neural networks, and applying pattern recognition techniques. Day-to-day tasks also include collaborating with cross-functional teams, analyzing datasets, and optimizing machine learning models to improve agricultural practices and outcomes.

Qualifications

• Proficiency in Pattern Recognition and Neural Networks
• Strong background in Computer Science and Algorithms
• Solid knowledge of Statistics
• Experience with machine learning frameworks and tools
• Excellent problem-solving and analytical skills
• Ability to work independently and in a team environment
• Experience in the agriculture industry is a plus
• Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field

• Design, develop, and implement machine learning models and algorithms.
• Collaborate with data scientists to preprocess data, select features, and train models.
• Deploy ML models into production environments, ensuring scalability and reliability.
• Monitor and maintain deployed models, making necessary adjustments and improvements.
• Optimize model performance for speed and efficiency.
• Develop and maintain ML pipelines and infrastructure.
• Stay current with the latest advancements in machine learning and AI research.
• Work with software engineering teams to integrate ML models into applications.
• Conduct experiments to evaluate different modeling approaches.
• Document ML models, methodologies, and results.

• Bachelor's or Master's degree in Computer Science, Engineering, Statistics, or a related quantitative field.
• Proven experience as a Machine Learning Engineer or similar role.
• Proficiency in programming languages such as Python, R, or Java.
• Strong experience with ML libraries and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Solid understanding of statistical modeling, data mining, and ML algorithms (e.g., regression, classification, clustering, deep learning).
• Experience with data preprocessing, feature engineering, and model evaluation.
• Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps principles.
• Excellent problem-solving and analytical skills.
• Strong communication and teamwork abilities.
• Must be able to work on-site in **Kisumu, Kisumu, KE**.

• Design, build, and deploy machine learning models and systems.
• Develop and maintain data pipelines for ML model training and inference.
• Implement and optimize ML algorithms using Python and relevant libraries.
• Collaborate with data scientists to translate research into production code.
• Perform feature engineering and model selection based on project requirements.
• Monitor deployed ML models for performance degradation and drift.
• Troubleshoot and resolve issues related to ML systems.
• Optimize ML models for performance, scalability, and efficiency.
• Stay current with the latest advancements in machine learning and AI.
• Document ML models, experiments, and deployment processes.
• Work with cloud platforms for ML model training and deployment.
• Contribute to the development of ML infrastructure and tooling.
• Ensure the ethical and responsible development of AI systems.

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related quantitative field.
• Minimum of 4 years of experience in machine learning engineering or a related role.
• Strong programming skills in Python.
• Proficiency with ML libraries such as TensorFlow, PyTorch, Keras, or scikit-learn.
• Experience with data preprocessing, feature engineering, and model evaluation.
• Familiarity with cloud platforms (AWS, Azure, GCP) and their ML services.
• Understanding of MLOps principles and tools.
• Excellent analytical and problem-solving skills.
• Strong communication and collaboration abilities.
• Ability to work independently and manage projects effectively in a remote environment.
• Experience with containerization (Docker) is a plus.

• Design, develop, and implement machine learning models and algorithms for various applications.
• Process, clean, and transform large datasets to prepare them for model training.
• Collaborate with data scientists and software engineers to integrate ML models into production systems.
• Develop and maintain robust ML pipelines for training, evaluation, and deployment.
• Monitor model performance in production and implement improvements and retraining strategies.
• Research and evaluate new ML techniques, tools, and technologies.
• Contribute to the development of AI strategy and roadmaps.
• Write clean, efficient, and well-documented code in Python or other relevant languages.
• Optimize ML models for performance, scalability, and efficiency.
• Stay abreast of the latest advancements in AI, machine learning, and deep learning.
• Collaborate effectively with cross-functional teams in a remote environment.
• Document research, experiments, and model details thoroughly.

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or a related quantitative field.
• Minimum of 4-6 years of experience in machine learning engineering or a related role.
• Proven experience in developing and deploying ML models into production environments.
• Strong programming skills in Python and proficiency with ML libraries/frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Solid understanding of statistical modeling, data mining, and algorithm development.
• Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
• Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and MLOps practices.
• Excellent problem-solving, analytical, and critical thinking skills.
• Strong communication and collaboration skills, adept at working in a distributed, remote team.
• Ability to work independently and manage project priorities effectively.
• This is a fully remote position, offering flexibility and the opportunity to work on groundbreaking AI projects from anywhere. Your contributions will be vital to our client's innovation efforts in areas impacting Malindi, Kilifi, KE .

• Design, develop, train, and deploy machine learning models and algorithms to solve complex business problems.
• Implement and maintain scalable ML infrastructure and pipelines for data processing, model training, and deployment.
• Collaborate with data scientists to translate research models into production-ready systems.
• Perform feature engineering, model selection, hyperparameter tuning, and performance evaluation.
• Develop and implement strategies for monitoring and maintaining ML models in production.
• Write clean, efficient, and well-documented code in languages such as Python.
• Stay up-to-date with the latest advancements in machine learning research, techniques, and tools.
• Contribute to the overall architecture and design of AI systems.
• Work with large datasets and distributed computing frameworks.
• Collaborate effectively with cross-functional teams in a remote environment.
• Identify opportunities for applying ML to improve products and processes.

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• Minimum of 5 years of professional experience in machine learning engineering or a related role.
• Strong programming skills in Python and experience with ML libraries and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Solid understanding of fundamental machine learning concepts, algorithms (e.g., supervised, unsupervised, deep learning), and statistical modeling.
• Experience with data processing and big data technologies (e.g., Spark, Hadoop).
• Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and MLOps practices.
• Excellent analytical, problem-solving, and critical thinking skills.
• Strong communication and collaboration skills, with the ability to work effectively in a distributed team.
• Experience with natural language processing (NLP), computer vision, or reinforcement learning is a plus.
• A proactive approach to learning and staying current with AI advancements.