About Careertakes

👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, Technology, Information and Internet.

Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.

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What You’ll Do

Confidential Client is hiring an experienced Machine Learning engineering leader to advance perception for autonomous systems. You will design, develop, and productionize sensor-fusion foundation models that provide real-time spatial and temporal understanding of the driving environment. This role partners closely with cross-functional teams (AI Foundation, Planning, Simulation, Research) to accelerate model development, reduce time-to-impact, and scale high-quality model deployment.

• Lead design and implementation of multi-modal/sensor-fusion foundation models for perception.
• Solve large-scale training and data pipeline challenges using extensive driving datasets.
• Optimize model training, evaluation, and deployment to meet strict latency and reliability requirements.
• Implement automated workflows for frequent model updates, validation, and rollout.
• Collaborate across engineering and research teams to integrate cutting-edge advances into production systems.
• Mentor engineers, set technical direction, and drive engineering excellence across the perception stack.

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Minimum Qualifications

• Master’s degree or PhD in Computer Science, Engineering, or related field.
• 10+ years of experience in machine learning model development and production.
• 4+ years building large-scale vision, video, or multi-modal foundation models.
• 6+ years working on ML-driven production systems involving large datasets, training at scale, and deployment.
• 6+ years of technical leadership experience in ML engineering organizations.
• 3+ years experience with computer vision models, large language models (LLMs), or vision-language models.
• Proficiency in Python and C++; production experience with PyTorch, JAX, or similar frameworks.
• Strong focus on automation, model quality, and practical systems engineering for low-latency inference.

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Nice-to-Have / Preferred Skills

• Deep experience with sensor fusion (lidar, radar, camera) and temporal modeling.
• Background optimizing distributed training pipelines and resource-efficient model tuning.
• Familiarity with simulation-driven training and real-world data augmentation strategies.
• Experience collaborating with research teams to transition models from prototype to production.

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Benefits & Compensation

• Base salary range: $349,000 — $431,000 USD (commensurate with experience and location).
• Eligibility for discretionary annual bonus and equity incentive plan.
• Comprehensive health, dental, and vision insurance.
• Generous paid time off and flexible/hybrid work arrangements.
• Professional development and ongoing learning opportunities.
• Work on high-impact projects at the intersection of machine learning and autonomous systems.

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Equal Opportunity & Hiring Transparency

Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.

If you have questions about how your data is used, please contact us directly.