Machine Learning Engineer
No salary listed
Mid
Master's, PhD
Southfield, MI, USA
In Person
AI & Machine LearningComputer Vision
Company Historically Provides H1B Sponsorship
About the job
Requirements
- A Master of Science or PhD in Computer Science, Machine Learning, Robotics, Computer Vision, or a related field is required.
- Strong software-engineering skills in Python and/or C++, with hands-on experience using PyTorch or equivalent deep-learning frameworks.
- A solid understanding of deep learning, computer vision, 3D geometry, multi-view reconstruction, sensor fusion, and transformer architectures is required.
- Experience developing detection, segmentation, tracking, depth, occupancy, or multimodal perception models is required.
- Experience building, evaluating, and deploying machine-learning systems using large-scale datasets is required.
- Ability to work independently and collaborate effectively across research, software, data, and vehicle teams is required.
Responsibilities
- Design and deploy production-scale auto-labeling solutions for 2D and 3D object detection, semantic and panoptic segmentation, lane and road-structure extraction, multi-object tracking, occupancy, scene understanding, and traffic-participant behavior.
- Develop automated label validation, confidence scoring, consistency checks, and quality-monitoring frameworks.
- Build active-learning and human-in-the-loop workflows that improve label quality while reducing manual annotation effort and turnaround time.
- Create teacher-student and model-assisted labeling workflows for large-scale camera and LiDAR datasets.
- Research, train, and evaluate camera-based and LiDAR-based detection, segmentation, tracking, depth-estimation, and occupancy models.
- Develop multimodal fusion models combining camera, LiDAR, radar, GNSS/IMU, and map context.
- Improve temporal consistency, calibration robustness, and long-tail performance across diverse driving environments and edge cases.
- Build end-to-end machine-learning workflows from raw sensor ingestion and preprocessing through annotation, quality control, and dataset delivery.
- Develop 3D Gaussian Splatting and related reconstruction pipelines for large-scale driving scenes collected from fleet vehicles.
- Use reconstructed scenes for label propagation, synthetic annotation generation, annotation validation, rare-case augmentation, and simulation.
- Create scene-centric representations that improve geometric accuracy and consistency across sensors, viewpoints, and time.
- Apply Vision-Language Models, Vision-Language-Action models, and multimodal foundation models to scene interpretation, label generation, verification, and edge-case discovery.
- Develop natural-language and agent-based workflows that help engineers search, inspect, curate, and validate large-scale datasets.
- Evaluate state-of-the-art research and convert promising methods into reliable production capabilities.
- Build scalable training and inference pipelines for fleet-scale datasets and distributed GPU infrastructure.
- Optimize model performance, throughput, reliability, monitoring, and reproducibility across cloud and production environments.
- Collaborate with perception, mapping, navigation, simulation, hardware, logging, and data-platform teams to deploy end-to-end solutions.
- Define and track metrics for labeling accuracy, coverage, throughput, cost, and operational efficiency.
Desired Qualifications
- Experience in autonomous driving, robotics, mapping, augmented/virtual reality, or spatial computing is preferred.
- Hands-on experience with 3D Gaussian Splatting, neural radiance fields, neural rendering, world models, or synthetic data generation is preferred.
- Experience building auto-labeling platforms, active-learning systems, human-in-the-loop workflows, or automated label-quality systems is preferred.
- Experience with camera-LiDAR fusion, depth estimation, 3D detection and tracking, and multimodal foundation models is preferred.
- Familiarity with Vision-Language Models, Vision-Language-Action models, Segment Anything Model family segmentation models, distributed computing, Docker, Kubernetes, continuous integration/continuous delivery, and cloud machine-learning infrastructure is preferred.
About the company
Lucid Motors designs and builds luxury electric vehicles in the United States for environmentally conscious customers who seek high performance and long range. It develops its own EV technology in house, including advanced motors and efficient designs that enable longer ranges with fewer batteries, making cars lighter and more sustainable. Lucid sells directly to consumers, bypassing traditional dealerships to control the entire experience from design and manufacturing to sales and service. The goal is to transform the automotive industry by advancing sustainable technology and delivering luxury, high-performance EVs with reduced environmental impact.
Company Size
5,001-10,000
Company Stage
IPO
Headquarters
Newark, California
Founded
2016
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Simplify's Take
What believers are saying
- On September 17, 2026, Lucid and Bolt targeted 25,000 autonomous European vehicles.
- On August 4, 2026, Lucid cut costs, boosting liquidity to $3.0 billion.
- Gravity deliveries and Europe expansion support higher mix, while Recharged CPO broadens ownership channels.
What critics are saying
- Lucid cut 18% of U.S. staff in June 2026, signaling demand and execution strain.
- Lucid delayed the midsize platform to second-half 2027, leaving Gravity as its lone growth engine.
- If Gravity volumes disappoint again, Lucid burns cash faster than Saudi support replenishes it.
What makes Lucid Motors unique
- Lucid's 900-volt architecture and in-house motors still deliver class-leading range in Air and Gravity.
- Lucid designs software-defined vehicles internally, letting Air UX 3.0 evolve faster than legacy rivals.
- Lucid's vertically integrated Arizona and Saudi factories control engineering, manufacturing, and customer experience.
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Benefits
- Family Medical Leave
- Remote Work Program
- Health & Wellness - Dental Benefits, Disability Insurance, Flexible Spending Account (FSA), Health Insurance Benefits, Life Insurance, Vision Benefits, Fitness Subsidies
- 401(K)
- Paid Volunteer Time
- Paid Holidays
- Paid Sick Days