Machine Learning Engineer

The TalentHaus; United States; Remote; USD 200,000 - 300,000; Full time

Benefits offered by this job

Medical insurance

Vision insurance

401(k)

Paid maternity leave

Child care support

Paid paternity leave

Tuition assistance

Job summary

A leading company is seeking a Machine Learning Engineer II to develop scalable models for autonomous vehicles. The candidate will work on real-time perception and predictive modeling, utilizing deep learning technologies. This role offers competitive compensation and opportunities to collaborate with top-tier professionals in a mission-driven environment focused on innovation.

Qualifications

• 5+ years of experience in applied machine learning or deep learning, preferably in AV or robotics.
• Proficiency with PyTorch, TensorFlow, and coding skills in Python/C++.
• Experience with computer vision models and large-scale datasets.

Responsibilities

• Design, train, and deploy deep learning models for real-time perception tasks.
• Build predictive modeling systems for behavior forecasting.
• Collaborate cross-functionally with teams to ensure model performance.

Skills

Deep Learning

Machine Learning

Computer Vision

Python

C++

Data Processing

Statistical Modeling

Education

Bachelor’s or Master’s degree in Computer Science, Robotics, or Electrical Engineering

Tools

PyTorch

TensorFlow

TensorRT

ONNX

Job description

This range is provided by The TalentHaus. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$200,000.00/yr - $300,000.00/yr

Additional compensation types

Annual Bonus and RSUs

Now Hiring: Machine Learning Engineer II (Autonomous Vehicles / Robotics) | Remote

About the Company

We're building the next generation of autonomous mobility systems to redefine how people and goods move through the world. Our platform powers fleets of self-driving vehicles operating in dynamic urban environments, and our machine learning team is at the core of this mission by developing scalable, production-grade models that enable real-time perception, prediction, and decision-making. As an MLE II, you'll contribute to building end-to-end ML systems for large-scale autonomy in designing, training, deploying, and optimizing models that allow vehicles to perceive their environment, anticipate intent, and respond safely and intelligently.

What You’ll Do

• Design, train, and deploy deep learning models for real-time perception tasks (e.g., object detection, semantic segmentation, sensor fusion, depth estimation).
• Build predictive modeling systems for behavior forecasting of pedestrians, cyclists, and vehicles.
• Optimize and scale ML pipelines across edge and cloud environments using tools like TensorRT, ONNX, and ROS.
• Contribute to data-centric AI efforts by developing labeling strategies, data augmentation techniques, and automated validation tools.
• Collaborate cross-functionally with robotics, software, and hardware teams to ensure model performance in simulation and on-vehicle testing.
• Conduct rigorous evaluations of model robustness, safety, and explainability in diverse edge cases.
• Participate in architecture reviews and actively shape the evolution of our ML infrastructure and tooling.
• 5+ years of experience in applied machine learning or deep learning (preferably in AV, robotics, or embedded systems).
• Proficiency with modern ML frameworks such as PyTorch or TensorFlow, and strong coding skills in Python and/or C++.
• Experience building and deploying computer vision models using camera, LiDAR, and radar data.
• Familiarity with 3D perception, point cloud processing, Kalman filtering, or multi-sensor fusion algorithms is a strong plus.
• Comfortable working with large-scale datasets, distributed training (e.g., PyTorch DDP or Ray), and GPU optimization techniques.
• Experience with edge deployment frameworks (TensorRT, TVM, ONNX) and embedded hardware constraints is preferred.
• Solid understanding of statistical modeling, overfitting/underfitting trade-offs, and model debugging techniques.
• Bachelor’s or Master’s degree in Computer Science, Robotics, Electrical Engineering, or related field; PhD a plus but not required.
• Work on real-world systems at the forefront of autonomous mobility
• Collaborate with world-class researchers, engineers, and roboticists
• Access to cutting-edge hardware, large-scale data, and live vehicle fleets
• Competitive compensation, bonus + equity, and benefits in a fast-moving startup backed by top-tier investors
• Mission-driven culture focused on safety, innovation, and impact

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Information Technology

• Industries

  Software Development

Referrals increase your chances of interviewing at The TalentHaus by 2x

Inferred from the description for this job

Medical insurance

Vision insurance

401(k)

Paid maternity leave

Child care support

Paid paternity leave

Tuition assistance

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