587 Machine Learning jobs in Kenya
Machine Learning Engineer
Posted 2 days ago
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Machine Learning Engineer
Posted 2 days ago
Job Viewed
Job Description
You will work closely with data scientists and software engineers to transform research prototypes into production-ready ML systems. This involves developing efficient data pipelines, selecting appropriate algorithms, and implementing scalable ML solutions. Experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn is essential, as is proficiency in Python. You will also be involved in feature engineering, model evaluation, and working with large datasets. The ability to optimize model performance and ensure the reliability of deployed systems is crucial. Strong analytical and problem-solving skills are required, along with excellent communication skills to collaborate effectively with cross-functional teams in a remote setting. A proactive approach to identifying and resolving challenges is highly valued.
Responsibilities:
- 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.
Machine Learning Engineer
Posted 2 days ago
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Job Description
Key Responsibilities:
- 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 .
Machine Learning Engineer
Posted 2 days ago
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Job Description
Responsibilities:
- 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.
Principal Machine Learning Engineer
Posted today
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Key Responsibilities:
- Lead the end-to-end development lifecycle of machine learning models, from data preprocessing and feature engineering to model training, evaluation, and deployment.
- Design and implement scalable and robust ML systems, ensuring efficient performance and reliability.
- Research and apply state-of-the-art machine learning algorithms and techniques to solve challenging business problems.
- Collaborate closely with data scientists, software engineers, and product managers to define ML requirements and integrate models into production environments.
- Develop and maintain production-level code for ML pipelines and infrastructure.
- Mentor and guide junior machine learning engineers, fostering a culture of technical excellence and continuous learning.
- Evaluate and select appropriate tools, frameworks, and technologies for ML development and deployment.
- Stay abreast of the latest advancements in AI and ML research and industry trends.
- Contribute to the strategic roadmap for AI and machine learning initiatives within the company.
- Present complex technical concepts and findings to both technical and non-technical audiences.
- Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or a related quantitative field.
- A minimum of 10 years of experience in machine learning engineering, with a significant focus on developing and deploying complex ML models in production.
- Deep expertise in various ML domains such as deep learning, reinforcement learning, natural language processing, and computer vision.
- Proficiency in programming languages such as Python, Java, or C++, and experience with ML libraries and frameworks like TensorFlow, PyTorch, scikit-learn, and Keras.
- Experience with cloud platforms (AWS, Azure, GCP) and distributed computing frameworks (e.g., Spark).
- Strong understanding of data structures, algorithms, and software engineering best practices.
- Proven ability to lead technical projects and mentor engineering teams.
- Excellent analytical, problem-solving, and critical-thinking skills.
- Exceptional communication and collaboration skills.
Senior Machine Learning Engineer
Posted today
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Senior Machine Learning Engineer
Posted 1 day ago
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Job Description
Key Responsibilities:
- Design, develop, and implement scalable machine learning models and algorithms.
- Clean, preprocess, and engineer features from large, complex datasets.
- Train, evaluate, and deploy ML models into production environments.
- Monitor model performance and implement strategies for continuous improvement and retraining.
- Collaborate with data scientists, software engineers, and product managers to define ML requirements and integrate solutions.
- Stay current with the latest advancements in machine learning research, techniques, and tools.
- Develop and maintain robust ML pipelines and MLOps practices.
- Write high-quality, well-documented code for ML solutions.
- Optimize ML models for performance, scalability, and efficiency.
- Contribute to the technical roadmap for AI and machine learning initiatives.
- Master's or Ph.D. in Computer Science, Statistics, Machine Learning, or a related quantitative field.
- Minimum of 7 years of experience in machine learning engineering or data science with a focus on model development and deployment.
- Expertise in programming languages such as Python and proficiency with ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Strong understanding of various ML algorithms (supervised, unsupervised, deep learning).
- Experience with MLOps tools and best practices for model deployment and lifecycle management.
- Proficiency in data manipulation and analysis using SQL and relevant libraries.
- Excellent analytical, problem-solving, and critical thinking skills.
- Strong communication and collaboration skills, with the ability to explain technical concepts to diverse audiences.
- Experience working in a remote, collaborative environment.
- Familiarity with cloud platforms (AWS, Azure, GCP) and their ML services is a plus.
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Remote Machine Learning Engineer
Posted 1 day ago
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Key Responsibilities:
- Design, build, train, and deploy scalable machine learning models.
- Develop and implement robust data pipelines for data collection, cleaning, and feature engineering.
- Collaborate with data scientists and researchers to translate models into production-ready code.
- Optimize ML algorithms and model performance for efficiency and accuracy.
- Implement and manage MLOps best practices, including continuous integration, continuous deployment (CI/CD), and model monitoring.
- Work with large datasets and distributed computing frameworks.
- Contribute to the architecture and design of ML systems.
- Stay up-to-date with the latest advancements in ML technologies, frameworks, and best practices.
- Troubleshoot and debug production ML systems.
- Document ML models, code, and processes thoroughly.
- Master's degree or Ph.D. in Computer Science, Machine Learning, Statistics, or a related quantitative field.
- Proven experience in developing and deploying machine learning models into production environments.
- Strong programming skills in Python and proficiency with ML libraries and frameworks such as TensorFlow, PyTorch, Scikit-learn, and Keras.
- Experience with MLOps tools and practices (e.g., Docker, Kubernetes, MLflow, Kubeflow).
- Solid understanding of data structures, algorithms, and software engineering principles.
- Experience with cloud platforms (AWS, Azure, GCP) and related ML services.
- Familiarity with big data technologies (e.g., Spark, Hadoop).
- Excellent analytical and problem-solving skills.
- Strong communication and collaboration skills, particularly in a remote team setting.
- Ability to work independently, manage priorities, and deliver high-quality results.
Senior Machine Learning Engineer
Posted 2 days ago
Job Viewed
Job Description
Responsibilities include designing, building, and maintaining scalable ML pipelines, experimenting with various algorithms and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn), and deploying models into production environments. You will work with large datasets, perform feature engineering, conduct rigorous model evaluation, and continuously iterate to improve performance. Collaboration with data scientists, software engineers, and product managers is key to translating research into production-ready solutions. A strong foundation in computer science, mathematics, and statistics is essential, along with expertise in programming languages such as Python. Experience with cloud platforms (AWS, Azure, GCP) and MLOps practices, including model monitoring, versioning, and automation, is highly desirable. The ideal candidate will have a proven track record of successfully delivering ML projects from conception to deployment. This is an exceptional opportunity to contribute to groundbreaking AI projects, working in a stimulating environment that encourages continuous learning and professional growth. The hybrid model allows for focused work at home coupled with productive team sessions at our office in Garissa. We foster a culture of innovation, where your contributions will directly impact the development of next-generation AI technologies. You will have the chance to mentor junior engineers and contribute to shaping the technical direction of our AI initiatives. Strong problem-solving skills and excellent communication abilities are crucial for success in this role. The hybrid nature of this role means candidates should be located within a commutable distance of our Garissa office for designated in-office days, typically 2-3 days per week, while enjoying the flexibility of remote work for the remainder of the week. We are dedicated to building diverse teams and encourage applications from all qualified individuals.
Location : Garissa, Garissa, KE
Lead Machine Learning Engineer
Posted 2 days ago
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Responsibilities:
- Design, develop, and implement advanced machine learning models and algorithms to solve complex business problems.
- Lead the end-to-end machine learning lifecycle, from data gathering and preprocessing to model training, evaluation, and deployment.
- Research and stay abreast of the latest advancements in machine learning, artificial intelligence, and data science.
- Develop and maintain robust ML pipelines for efficient model training and deployment.
- Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to define project requirements and deliver impactful solutions.
- Mentor and guide junior ML engineers and data scientists, fostering a culture of innovation and continuous learning.
- Evaluate and select appropriate ML tools, libraries, and frameworks for different projects.
- Optimize ML models for performance, scalability, and efficiency in production environments.
- Contribute to the development of the company's AI strategy and roadmap.
- Present technical findings and recommendations to stakeholders.
- Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- Proven experience (5+ years) in designing, developing, and deploying machine learning models in production.
- Expertise in Python and ML libraries such as TensorFlow, PyTorch, scikit-learn.
- Strong understanding of various ML algorithms (e.g., deep learning, NLP, computer vision, reinforcement learning).
- Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (AWS, Azure, GCP).
- Familiarity with MLOps practices and tools.
- Excellent programming skills and experience with software development best practices.
- Strong leadership and communication skills, with the ability to mentor and inspire a team.
- Ability to work effectively in a fully remote, collaborative environment.
- Demonstrated ability to translate complex problems into actionable ML solutions.