Our Careers
Machine Learning Engineer
As a Machine Learning Engineer at Inspxtra.ai, you will play a pivotal role in developing and refining our AI-driven inspection solutions. You will work alongside a talented team of engineers and data scientists to enhance our computer vision algorithms, enabling our platform to detect vehicle damages with unprecedented accuracy and speed. You will have the opportunity to directly impact the evolution of our products, working in an innovative and fast-paced environment.
Develop and Implement Machine Learning Models:
- Design, train, and deploy machine learning algorithms and models focused on computer vision tasks such as damage detection, object recognition, and anomaly detection in vehicle imagery.
Collaborate with Cross-Functional Teams:
- Work closely with product managers, software engineers, and AI researchers to understand requirements and deploy machine learning models effectively into our platform and services.
Data Processing and Feature Engineering:
- Work with large datasets, clean and preprocess image data, extract features, and engineer improvements that optimize model performance.
Model Optimization and Tuning:
- Continuously monitor and fine-tune machine learning models to improve accuracy, speed, and scalability. Conduct experiments to evaluate the effectiveness of different models and architectures.
Deploy and Scale Models:
- Implement models into production systems, ensuring that they are scalable, reliable, and integrated seamlessly with existing technology stacks.
Stay Up-to-Date with AI/ML Trends:
- Research and explore the latest advancements in AI, machine learning, and computer vision to ensure the team’s solutions remain state-of-the-art.
Documentation and Reporting:
- Provide clear and concise documentation for models, algorithms, and experiments. Present technical findings to non-technical stakeholders to help shape product strategies.
Education:
- Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field. PhD is a plus.
Experience:
- Proven experience (2+ years) in building and deploying machine learning models, especially in computer vision.
- Solid experience with deep learning frameworks like TensorFlow, Keras, or PyTorch.
- Experience in training and optimizing models on large image datasets.
Technical Skills:
- Proficiency in Python, with experience in machine learning libraries (e.g., scikit-learn, OpenCV, etc.).
- Strong understanding of neural networks, CNNs (Convolutional Neural Networks), and other advanced machine learning techniques.
- Experience with cloud platforms (AWS, Google Cloud, etc.) and tools for deployment (Docker, Kubernetes).
- Strong understanding of model evaluation metrics and debugging techniques.
Soft Skills:
- Strong problem-solving abilities and attention to detail.
- Excellent communication and collaboration skills.
- Passion for innovation and willingness to explore new technologies.
- Ability to work in a fast-paced, dynamic environment and meet deadlines.
- Experience with automotive-related datasets (e.g., images of vehicles, damage detection) is a plus.
- Familiarity with edge computing and deploying ML models in resource-constrained environments (e.g., mobile or embedded devices).
- Knowledge of reinforcement learning, GANs, or transfer learning techniques.
Impact:
Be part of a growing company that’s revolutionizing an entire industry.
Innovation:
Work on cutting-edge AI technologies and solve complex, real-world problems.
Culture:
Join a collaborative, inclusive, and dynamic team that values creativity and growth.
Flexibility:
Flexible working hours and remote work options available.
Career Growth: Opportunities to grow and advance within a fast-paced, innovative company.