Highlights
End-to-end model development, cutting-edge GenAI tools, cloud/edge deployment, innovation in video safety.
Description
Job Summary
pJoin our Machine Learning team at Lytx to develop and deploy advanced ML/DL models for video safety monitoring. This role involves end-to-end model development, optimization, and deployment on cloud/edge platforms. You'll work with cutting-edge GenAI tools to build innovative solutions and enhance overall safety in the transportation industry.
Responsibilities
- Develop ML/DL models from problem formulation to evaluation
- Implement and debug DL models using PyTorch or TensorFlow
- Optimize and deploy models on cloud/edge platforms
- Leverage GenAI tools for internal and customer applications
- Build prompt engineering workflows and RAG pipelines
- Communicate technical findings to cross-functional teams
Required Skills
- Data Engineering
- Machine Learning Frameworks (PyTorch/TensorFlow)
- Python Programming
- GenAI Tools & APIs
- Model Optimization Techniques
Required Skills Explained
- Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field.
- Experience in developing ML/DL models end-to-end from problem formulation to deployment.
- Familiarity with DL frameworks like PyTorch or TensorFlow for model implementation and debugging.
- Proficiency in Python programming language; experience with C/C++ is a plus.
- A strong foundation in mathematics, probability, statistics, and algorithms.
- A solid understanding of core ML concepts including supervised/unsupervised learning, model evaluation, and regularization.
- The ability to work collaboratively in a fast-paced environment with strong analytical and problem-solving skills.
Who is this for
pWe are seeking a skilled Machine Learning Engineer to join our team. Ideal candidates have experience with ML/DL and are passionate about building innovative solutions that enhance road safety. You should thrive in a fast-paced environment and enjoy working collaboratively.
Why This Job is a Good Opportunity
ulliWork on cutting-edge technology that impacts road safety globally.liJoin a team of innovative professionals contributing to the advancement of AI in telematics.liPotential to use GenAI tools and LLM APIs to build applications for internal and customer-facing needs.liThe opportunity to deploy models on cloud/edge platforms, optimizing performance and scalability.liA supportive work environment with a mission-driven culture focused on safety and innovation.
Interview Preparation Tips
- Prepare examples of your previous experience in developing ML/DL models from problem formulation to deployment.
- Showcase proficiency in using DL frameworks such as PyTorch or TensorFlow through relevant projects or internships.
- Highlight your understanding of core ML concepts and how you can apply them in real-world scenarios.
- Discuss any experience you have with model optimization, debugging, and deployment on cloud/edge platforms.
- Bring examples of times when you successfully worked on complex problem-solving tasks in a team environment.
Career Growth in This Role
pGrowth opportunities within the role include advancing to senior machine learning engineer positions or specializing in specific areas such as computer vision or natural language processing. The company's focus on continuous improvement and innovation provides ample opportunities for learning new technologies and contributing to the development of state-of-the-art solutions.pEmployees can also transition into leadership roles, including team leads or project managers, by demonstrating their technical expertise and managerial skills. Additionally, there are opportunities to collaborate with cross-functional teams, enhancing career versatility.
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Frequently Asked Questions
What is the salary range?The salary range is 3 LPA.
Is relocation assistance provided?Relocation assistance may be available for eligible candidates.
Are there opportunities for growth within the company?Yes, we offer career advancement opportunities and continuous learning resources.
