711 Autonomous Driving Systems jobs in Kenya

• Define and document the overall software architecture for autonomous driving systems.
• Lead the design and implementation of robust, real-time software solutions for ADAS and autonomous driving features.
• Collaborate closely with hardware engineers, AI/ML specialists, and systems engineers to ensure seamless integration.
• Establish software development best practices, coding standards, and review processes.
• Identify and mitigate technical risks associated with complex software development projects.
• Evaluate and select appropriate software technologies and tools.
• Provide technical leadership and mentorship to the software engineering team in a remote setting.
• Ensure compliance with automotive safety standards (e.g., ISO 26262).
• Contribute to the continuous improvement of the software development lifecycle.

• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field.
• Extensive experience in automotive software development, with a significant focus on ADAS or autonomous driving systems.
• Proven expertise in software architecture design for real-time embedded systems.
• Proficiency in C++, Python, and embedded software development tools.
• Deep understanding of vehicle communication protocols (e.g., CAN, Automotive Ethernet).
• Experience with sensor fusion, path planning, and control algorithms.
• Strong knowledge of software development methodologies (Agile, Scrum).
• Excellent analytical and problem-solving skills.
• Exceptional ability to communicate technical concepts effectively in a distributed team environment.
• Previous experience leading software teams is highly desirable.

• Define system-level requirements for autonomous driving features, including perception, planning, and control subsystems.
• Architect and design automotive electronic systems, ensuring compliance with safety standards (e.g., ISO 26262).
• Develop and integrate software modules for autonomous driving functions, utilizing C++ and Python.
• Collaborate with hardware engineers to select and test sensors (LiDAR, radar, cameras) and compute platforms.
• Implement and validate sensor fusion algorithms to create a comprehensive environmental model.
• Develop and refine control strategies for vehicle motion and path planning.
• Participate in vehicle testing and validation activities, both in simulation and on-road.
• Analyze test data, identify system issues, and implement corrective actions.
• Work with CAN, LIN, Automotive Ethernet, and other relevant communication protocols.
• Contribute to the continuous improvement of development processes and tools.
• Mentor junior engineers and share expertise in automotive systems engineering.

• Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or a related field.
• 6+ years of experience in automotive systems engineering, with a focus on ADAS or autonomous driving.
• Proven experience in C++ and Python programming for embedded systems.
• In-depth knowledge of automotive communication protocols (CAN, LIN, Automotive Ethernet).
• Experience with sensor technologies (LiDAR, radar, cameras) and sensor fusion techniques.
• Familiarity with real-time operating systems (RTOS) and embedded software development.
• Experience with automotive safety standards (e.g., ISO 26262).
• Strong analytical and problem-solving skills.
• Ability to work effectively in a fully remote, collaborative environment.
• Excellent communication and interpersonal skills.

• Define system requirements and architectures for autonomous driving systems.
• Integrate and validate AD software and hardware components.
• Develop and refine AD algorithms for perception, sensor fusion, planning, and control.
• Collaborate with cross-functional teams in a remote setting.
• Ensure the safety, reliability, and performance of AD systems.
• Support vehicle testing and validation activities.
• Troubleshoot and resolve complex system-level issues.
• Contribute to the development of AD standards and best practices.
• Mentor junior engineers and share technical expertise.
• Stay current with the latest advancements in autonomous driving technology.

• Master's degree or Ph.D. in Computer Science, Electrical Engineering, Mechanical Engineering, or a related field.
• 5+ years of experience in automotive systems engineering, with a focus on autonomous driving.
• Proven experience with AD sensor technologies (LiDAR, radar, cameras, IMU).
• Strong understanding of AD software development, including C++, Python, ROS.
• Experience with simulation tools and methodologies for AD testing.
• Knowledge of functional safety (ISO 26262) and SOTIF.
• Excellent analytical, problem-solving, and debugging skills.
• Strong communication and collaboration skills for remote work.
• Ability to work independently and manage project timelines effectively.

Role Overview:

We are looking for a Senior AI/Machine Learning Engineer (7+ years of experience) who is a stellar individual contributor with recent hands-on expertise in fine-tuning and large-scale training of modern models (LLMs/VLMs).

This is a hands-on role where you will :

• Lead fine-tuning workflows, large-scale training runs, and evaluation design.

• Collaborate closely with researchers to bring cutting-edge approaches from papers into production.

• Work directly with customers to align performance metrics, validation, and deployment readiness.

Note: This is not a managerial role. We are seeking candidates who are currently active ICs, heavily involved in model fine-tuning/training in the last 8–12 months.

What You'll Do Day-to-Day

• Fine-tune and train LLMs/VLMs at scale (LoRA/QLoRA, PEFT methods).

• Build reproducible training pipelines with distributed training and mixed precision.

• Design and run robust evaluation frameworks (task-specific + lm-eval-harness).

• Translate research papers into working implementations, collaborating with researchers.

• Work with customers to validate models against business and performance needs.

• Optimize training runs with profiling, performance tuning, and efficiency improvements.

• Maintain experiment tracking, reproducibility, and structured model artifacts.

Requirements

• 7+ years in ML/AI engineering, with a strong recent focus on fine-tuning and training large models.

• Expert in PyTorch, Hugging Face Transformers, and PEFT (LoRA/QLoRA).

• Strong experience with distributed training (DDP, FSDP, DeepSpeed, Accelerate).

• Skilled with evaluation frameworks (lm-eval-harness, custom metrics, task benchmarks).

• Proven ability to reproduce and improve results from recent research papers.

• Strong coding practices in Python, with modular, clean implementations.

• Familiarity with experiment tracking tools (Weights & Biases, MLflow).

• Ability to interact with customers and researchers to translate requirements into engineering solutions

(Bonus) Preferred Qualifications:

• Experience with other ML libraries (e.g., PyTorch, Flax)
• Background in ML research or scientific computing
• Experience with production model monitoring and governance

• Lead the design, integration, and validation of autonomous driving systems.
• Define system requirements and architectures for ADAS and autonomous functions.
• Oversee the integration of sensors, ECUs, software, and actuators.
• Ensure compliance with functional safety (ISO 26262) and SOTIF standards.
• Develop and execute system validation plans, including simulation and vehicle testing.
• Collaborate with software, hardware, and testing teams.
• Analyze system performance data and identify areas for improvement.
• Troubleshoot complex system integration issues.
• Mentor junior engineers and provide technical leadership.
• Stay abreast of emerging technologies in autonomous driving.

• Bachelor's or Master's degree in Electrical Engineering, Mechanical Engineering, Computer Science, or a related field.
• Minimum of 7 years of experience in automotive systems engineering, with a strong focus on ADAS/autonomous driving.
• Proven experience in system design, integration, and validation for automotive applications.
• In-depth knowledge of sensor technologies (LiDAR, radar, cameras), sensor fusion, and control systems.
• Familiarity with functional safety (ISO 26262) and SOTIF.
• Experience with simulation tools and hardware-in-the-loop (HIL) testing.
• Strong analytical, problem-solving, and critical thinking skills.
• Excellent leadership, communication, and interpersonal skills for remote team management.

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**.