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About the position At Phantom AI, weve built a team of incredibly talented and ambitious people challenging the norm in the automotive industry. We are building cost-effective L2/L3 solutions to reduce the burden of everyday driving and make the roads safe for everyone. For instance, we believe democratizing technologies such as Automatic Emergency Braking and Emergency Lane Support is the first priority before tackling a fully self-driving vehicle. Our main customers are Tier 1 automotive manufacturers who are focused on delivering L2/L3 solutions and in the future will deliver full autonomy. We differentiate ourselves from other autonomous driving startups through a combination of state-of-the-art technological know-how and real automotive experiences of shipping ADAS systems at a volume production scale. If you feel that you have the passion, commitment, and drive to challenge the status quo within the automotive industry, we would love to hear from you. We are seeking a highly skilled Senior Deep Learning Engineer to drive the development and deployment of advanced perception models for Advanced Driver Assistance Systems (ADAS). The successful candidate will play a key role in designing cutting-edge neural network architectures, optimizing model performance, and ensuring reliable deployment on embedded platforms. This position requires a balance of deep technical expertise, strong analytical thinking, and cross-functional collaboration. Responsibilities Design and implement advanced deep learning architectures to enhance perception capabilities within ADAS systems. Maintain and continuously improve existing models by optimizing performance, addressing issues, and refining architecture and algorithms. Perform detailed root cause analysis of production issues and develop sustainable, high-quality solutions. Optimize model performance with a focus on latency, efficiency, and resource utilization for real-time embedded deployment. Integrate and validate deep learning algorithms on automotive-grade hardware and embedded SoCs. Collaborate closely with data engineering, data annotation, and platform engineering teams to ensure smooth data flow and seamless model integration. Provide regular updates and technical reports on model development, maintenance progress, and performance metrics to management. Requirements 35+ years of professional experience developing, training, validating, and deploying deep learning-based perception models for ADAS or related computer vision applications. In-depth understanding of training and inference pipelines, including data loading, augmentation, and loss function design. Advanced degree (M.S. or Ph.D.) in Computer Vision, Robotics, Machine Learning, or a closely related discipline, or equivalent industry experience. Strong proficiency in Python and a deep understanding of software design principles and development best practices. Expertise in PyTorch (preferred) or TensorFlow for large-scale model development and experimentation. Practical experience with data pipelines, distributed training, and machine learning experiment management tools. Proven ability to work effectively in a collaborative, cross-functional team environment. Nice-to-haves Comprehensive understanding of machine learning algorithms, including classification, regression, and clustering methods. Experience deploying and optimizing models for embedded or automotive SoCs (e.g., NVIDIA Drive, TI TDA4, Qualcomm Snapdragon). Proficiency in model optimization techniques such as quantization, pruning, and knowledge distillation. Doctorate (Ph.D.) in Computer Science, Artificial Intelligence, or related field is a plus. Strong programming experience in Python and/or C++ within Linux development environments. Familiarity with automotive perception workflows, datasets, and evaluation frameworks (e.g., KITTI, Waymo, Euro NCAP) Benefits Salary \$180,000-\$240,000 Medical, dental and vision coverage Office snacks & reimbursable meals Paid Time Off FSA 401K Apply To this Job .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.