Location: Palo Alto, CA

About Metamorphic

Metamorphic is developing new approaches to intelligence by combining machine learning with large-scale experimental neuroscience, informed by the principles that make the brain efficient, flexible, and robust. We are building foundation models trained on rich, continuous neural data — a high-resolution model of the brain at a scale never before possible.

Our founding team spans machine learning, neuroscience, and neurotechnology, with prior work including the MICrONS project, Neuropixels, and the Enigma project, as well as foundational scientific contributions in learning, neural computation, and generative modeling. Our work sits at the frontier of AI research, and we believe the highest-impact discoveries will come from researchers and engineers working as a single, tightly collaborative team.

The name Metamorphic reflects our belief that the next advances in intelligence will come from a change in form, beyond scale — from artificial to natural intelligence.

About the Role

If there is a role that is not listed (here), but you believe that you are a strong fit for Metamorphic's vision and mission, we are always open to general applications from exceptional talent. Please use the question asking why you are interested in Metamorphic to pitch us on your ideal full-time position or internship.

Helsinki, Finland

Computer Vision Engineer, Spectacular AI

Spectacular AI is looking for computer vision and software engineers to extend the capabilities of our cutting-edge GNSS-free UAV navigation system. We offer tough technical challenges and a chance to work closely with interesting customers with real-world impact.

Working alongside our team, you will help bridge the gap between academic breakthroughs and robust production code. This role is an ideal fit if you possess a strong theoretical understanding of modern computer vision methods paired with solid programming skills.

Areas of interest include:

• SLAM, sensor fusion, photogrammetry, and visual localization
• VLMs, multimodal foundation models, and novel view synthesis
• Guidance, navigation and control

Requirements

• A completed MSc or higher degree in a relevant STEM field (e.g., Computer Science, Electrical Engineering, Mathematics, Physics).
• Good Python programming skills and at least basic knowledge of Git and Linux.
• Hands-on experience with VIO, SLAM, INS or photogrammetry, or modern computer vision methods such as Dust3r, VGGT, and ACE Zero is considered a significant advantage.
• You should be capable of contributing to the field at a level consistent with top-tier research publications.
• Fluency in English.
• Readiness to relocate to the Helsinki region, Finland for full-time, in-person work in our Espoo office.
• Legal right to work in the EU. Visa sponsorships for non-EU applicants are not available.

Ideal Extras

The following skills, qualifications and experience are not mandatory but highly valued:

• A PhD degree.
• Software engineering best practices, CI/CD, build systems, or C++ skills.
• Experience with libraries such as Eigen, Ceres, GTSAM, g2o, or OpenCV.
• Embedded camera systems, sensors, or electronic/mechanical engineering.
• Domain knowledge: Aviation, UAVs, Geographic Information Systems (GIS).

To apply, please send your resume and a cover letter to careers@spectacularai.com.

Staff Machine Learning Engineer - Road & Lane Detection

Job ID: 102402
Location: Hybrid in Montreal, Quebec or Ann Arbor, MI; Remote in the United States or Canada
Apply: View and apply through Torc Careers

What You’ll Do

• Own the model roadmap for Road & Lane Detection within the Model Dev ML organization, from concept through production-grade model maturity.
• Research, design, and train advanced neural architectures, including multi-camera BEV transformers, LiDAR-vision fusion models, and topological lane graph networks.
• Lead data strategy for this domain, including data curation, labeling policies, and active learning pipelines to capture long-tail scenarios such as occlusions, complex merges, and construction zones.
• Develop robust metrics and evaluation frameworks for lane and road geometry accuracy, temporal consistency, and cross-domain generalization.
• Advance foundational capabilities such as self-supervised pretraining, synthetic-to-real adaptation, and temporal modeling for road and lane understanding.
• Drive large-scale experiments by designing, running, and analyzing results from distributed training workflows and ablations to identify scalable improvements.
• Collaborate with other model development and perception teams to ensure model coherence and interface consistency.
• Mentor engineers and scientists, setting best practices for model training, evaluation, and code quality.
• Stay ahead of the research frontier by evaluating and adapting emerging techniques, such as BEV-based large models, vectorized map prediction, and lane graph transformers, to production-grade perception.

What You’ll Need to Succeed

• 10+ years of experience developing deep learning models for perception or computer vision at scale.
• M.S. or Ph.D. in Computer Science, Electrical Engineering, Robotics, or a related field, or equivalent experience.
• Deep expertise in semantic and instance segmentation, BEV modeling, or scene topology estimation.
• Strong understanding of lane and road geometry modeling, camera calibration, and sensor projection.
• Proficiency with Python and modern ML frameworks such as PyTorch or Lightning.
• Experience with distributed training pipelines, experiment management, and large-scale dataset handling.
• Proven leadership in guiding technical roadmaps, mentoring engineers, and driving measurable model improvements.

Bonus Points

• Experience developing ML models for autonomous driving, mapping, or ADAS systems.
• Familiarity with multi-modal fusion, including camera, LiDAR, radar, and HD maps.
• Hands-on experience with BEV-based and topological prediction models.
• Contributions to perception-related ML research, including CVPR, NeurIPS, ICCV, ICLR, or ICRA.
• Strong intuition for data quality, bias mitigation, and uncertainty modeling.

US Pay Range: $219,700 - $329,600 USD

Please click on the link for full job description

What You Will Do

Build and Lead the Engineering Organization

• Lead a multi-team engineering organization of ML engineers and engineering managers; recruit, hire, develop, and retain senior technical and leadership talent, and build a culture of engineering rigor and delivery discipline.
• Hiring at scale is a material part of this role — Firefly Foundry is growing rapidly, and sustaining scaling momentum depends on it. You will integrate top technical and leadership talent into the organization at the pace the business demands.
• Establish the engineering bar, the bench, and the talent strategy that let Firefly Foundry sustain 10x growth in capability breadth and traffic without linear headcount growth.
• Define the operating rhythm — goal-setting, exec reviews, and engineering reviews — that keeps a fast-scaling org coordinated.

Define and Own the Technical Strategy

• Own the multi-year architecture for training and inference at scale: pipeline construction, data pipelines, evaluation frameworks, model lifecycle management, and accelerator utilization (CUDA, NCCL, and the wider GPU stack).
• Set the strategy for fast model deployment, parallel pipeline operation at scale, tenancy/data isolation, and self-serve capability buildout.
• Make the build-vs-buy and prioritization calls on emerging GenAI techniques in partnership with Applied Science, based on material improvements in capability, cost, or speed.

Own Production Reliability and Economics

• Hold the line on production SLAs for orchestrated and deployed model services.
• Own analytics and observability across every model pipeline — quality, latency, cost, and utilization.
• Drive cost-to-serve down on a multi-year curve while expanding capability.

Drive Customer and Partner Outcomes

• Represent engineering in technical customer engagements with enterprise customers — translating creative and business requirements into ML roadmaps, milestones, and success metrics.
• Co-design scalable, cost-efficient serving for real-time on-set use cases and high-volume social content generation, in partnership with infrastructure and platform teams.
• Steward the GPU vendor and hyperscaler relationships that underwrite Firefly Foundry's serving capacity.

What You Bring

Leadership Scope

• 10+ years in applied machine learning and ML systems, including 5+ years leading engineering organizations — with prior experience leading managers of managers.
• Demonstrated success shipping generative AI products in production at enterprise scale.
• Proven ability to operate as a peer to VP-level partners across product, science, infrastructure, and field organizations, and to represent engineering credibly in front of senior customer and partner executives.
• Track record of building engineering benches, defining career frameworks for emerging roles, and developing leaders who themselves become directors.

Technical Judgment

• Deep understanding of the modern generative model landscape (diffusion, transformers, VAEs, latent video models, control/adapters, or similar) — enough to make architecture, investment, and prioritization calls with confidence, in close partnership with Applied Science.
• Strong intuition for the economics and engineering reality of large-scale inference: accelerator stacks, model optimization and quantization, and the tradeoffs between quality, latency, and cost.
• Experience designing and operating ML systems end-to-end — data, training, evaluation, deployment, monitoring, and continuous improvement — at production scale.
• Familiarity with high-resolution media pipelines (4K+ video, high bit-depth) or adjacent bandwidth- and latency-sensitive domains is a meaningful plus.

Location: Mountain View, CA

Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all. We’re searching for a Staff Machine Learning Engineer - Online Maps to join Aurora’s Maps ML team. The Maps ML team is responsible for providing map data to the Aurora driver in the face of real-time world changes.

In this role, you will...

-Lead and Collaborate with other members of the Online Maps autonomy team to improve/ideate and implement perception algorithms that power the Aurora Driver -Research and develop state-of-the art deep learning/machine learning models to improve our perception solutions under challenging and diverse scenarios -Develop novel verification and validation technologies and techniques -Partner with engineers from online maps, simulation, and safety to ensure that online mapping technology is ready for operation with no vehicle operator -Build infrastructure and tests that support critical go/no go decisions for deploying the Aurora Driver -Integrate, test, and deploy production-ready solutions into the production code that powers the Aurora Driver

Required Qualifications:

-Excellent software engineering skills in Python and/or C++ -Extensive exp in any deep learning framework, such as PyTorch -Extensive exp in Computer Vision, Machine Learning, Deep Learning, or other relevant areas of Artificial Intelligence (e.g., as evidenced by industry experience, publication record)

Desirable Qualifications:

-Relevant industry experience (prior work on self-driving vehicles, autonomy, and/or robotics projects) -Contributions to open source project(s) -Strong track record in any field related to machine learning, as evidenced by top-tier publications -Examples of relevant fields and conferences: computer vision (e.g., CVPR, ECCV, ICCV, IJCV), machine learning (e.g., ICML, NeurIPS, JMLR, PAMI), robotics (e.g., RSS, IJRR), graphics (e.g., SIGGRAPH, TOG

Novi Sad, Serbia. We will cover the relocations costs and visa requirements

Our team is global, addressing the challenges of bringing safe ADAS and autonomous automotive systems to market for our customers.

We are seeking a visionary Senior Computer Vision & AI Engineer to bridge the gap between traditional perception and the next generation of autonomous intelligence. In this role, you will lead the development of high-performance ML models—ranging from core ADAS detection tasks to sophisticated Visual Language Models (VLMs). You will play a pivotal role in evolving our autonomous driving stack, turning complex camera data into actionable intelligence that ensures safety and innovation on the road. 

Responsibilities - Design and implement machine learning algorithms for object detection, tracking, and classification using camera data - Develop and optimize computer vision algorithms for tasks such as lane detection, traffic sign recognition, and pedestrian detection - Work closely with cross-functional teams to integrate machine learning models into existing systems - Stay up-to-date on the latest advancements in machine learning and computer vision and apply them to real-world problems - Analyze and improve the performance of existing machine learning models - Contribute to the development of innovative camera vision solutions for advanced driver assistance systems (ADAS) and autonomous driving - Design and build Visual Language Models

⠀Must Have - Ph.D. in Computer Science, Machine Learning, or a related field - Strong understanding of machine learning algorithms, including deep learning and convolutional neural networks - Extensive experience in computer vision, image processing, and object recognition - Proficiency in programming languages such as Python and C++ - Experience with deep learning frameworks such as TensorFlow or PyTorch - Strong problem-solving and analytical skills - Ability to work independently and as part of a team

⠀Nice to have - Familiarity with automotive-grade standards and safety-critical applications is a plus

What We Offer Each employee has a chance to see the impact of his work. You can make a real contribution to the success of the company.
Several activities are often organized all over the year, such as weekly sports sessions, team building events, monthly drink, and much more

Location: Mountain View CA or Pittsburgh PA

We are looking for a Senior Staff Software Engineer to join our Performance Engineering and Optimization (PeO) team. As a technical leader in this high-impact group, you will spearhead efforts to push the boundaries of our system's efficiency, ensuring our technology remains at the forefront of the industry. This is a rare opportunity to own the performance roadmap for a commercialized product, tackling complex, large-scale engineering challenges that directly influence the reliability and speed of our fielded environment.

In this role you will:

-Lead cross-functional performance initiatives to identify and resolve systemic bottlenecks, significantly improving end-to-end latency and system throughput. -Architect and implement advanced system instrumentation frameworks to provide deep visibility into modern OS-level performance metrics. -Drive the technical strategy for C/C++ optimization, mentoring junior engineers and establishing best practices for high-performance systems-level programming. -Collaborate with product and infrastructure teams to ensure that performance remains a core pillar throughout the product lifecycle, from initial design to field deployment. -Analyze and interpret complex telemetry data from fielded environments to proactively address performance regressions and optimize resource utilization.

Required qualifications:

-8–10+ years of professional experience in systems-level programming -Lead C/C++ optimization and system instrumentation to improve latency and throughput. -Experience delivering and supporting a commercialized product in a fielded environment. -Hands-on expertise with modern OS-level instrumentation toolkits

Desirable qualifications:

-Proven track record of technical leadership for large-scale performance engineering projects within the autonomous vehicle or robotics industry. -Deep familiarity with Linux kernel internals, memory management, and hardware-software co-design principles. -Experience with specialized profiling tools (e.g., eBPF, perf, or Ftrace) and automated performance regression testing suites. -Advanced degree (Master’s or PhD) in Computer Science, Computer Engineering, or a related field with a focus on systems performance.

Foster City, CA

The Prediction & Behavior ML team is responsible for developing machine learning (ML) algorithms that learn and predict behaviors from data, applying them both on-vehicle to influence driving behavior and off-vehicle to provide ML capabilities to simulation and validation. Given the tight integration of behavior forecasting and motion planning, our team collaborates closely with the Planner team to advance overall vehicle behavior. We also work closely with our Perception, Simulation, and Systems Engineering teams to accelerate our ability to validate our driving performance.

As a Learned Trajectory Machine Learning Engineer you will be responsible for developing deep learned models that produce trajectories for our vehicles to drive. Given the tight integration of behavior prediction and motion planning, you will closely collaborate with the Planner and Perception teams in the advancement of our overall vehicle behavior. In this role, you will: You will develop new deep learning models that use imitation learning and reinforcement learning to generate driving plans for our autonomous vehicle. You will also work on techniques to estimate the quality of those driving plans along the dimensions of safety, progress, comfort etc. You will leverage our large-scale machine learning infrastructure to discover new solutions and push the boundaries of the field You will develop metrics and tools to analyze errors and understand improvements of our systems You will collaborate with engineers on Perception, Planning, and Simulation to solve the overall Autonomous Driving problem in complex urban environments Qualifications BS, MS, or PhD degree in computer science or related field Experience with training and deploying transformer-based model architectures and reinforcement learning Experience with production Machine Learning pipelines: dataset creation, training frameworks, metrics pipelines Fluency in Python with a basic understanding of C++ Extensive experience with programming, algorithm design, and strong mathematics skills Bonus Qualifications Conference or Journal publications in Machine Learning or Robotics related venues Prior experience with Prediction and/or autonomous vehicles or robotics in general $277,000 - $407,000 a year Base Salary Range

There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.

Role: Robotics Software - Perception ML Engineer Location: SF Bay Area (in-person)

About the role

We’re looking for an experienced Perception ML Engineer to join our team. As an early member, you will play a pivotal role in building and shaping the AI capabilities of our robots. You will work on challenging problems around manipulation and navigation in dynamic outdoor environments. You'll need to thrive in a fast-paced startup environment where you'll wear multiple hats and have a direct impact on our product's evolution. Ideally, you have a proven track record of developing and deploying perception ML systems in production, and you're passionate about pushing the boundaries of what's possible in robotics with AI.

What you’ll get to work on

• Develop and deploy state-of-the-art perception models for challenging manipulation and navigation problems.
• Help drive our technical approach, with particular focus on real-world deployments.
• Research and develop techniques around 3D scene understanding, detection, segmentation, pose and world/video models.
• Develop robust metrics to establish performance of large vision models.
• Work with multimodal data (e.g. cameras, LIDAR, tactile).
• Develop and improve real/synthetic data pipelines for challenging perception problems.
• Build scalable training and validation infrastructure.
• Collaborate with other teams in the company.

What we look for

• M.S/Ph.D degree in robotics, vision, computer science, mechanical engineering, electrical engineering or other engineering disciplines (or equivalent experience).
• 4+ years of hands-on experience developing perception solutions for robotics applications like manipulation and navigation.
• Experience working on one or more of detection, segmentation, pose estimation, tracking, 3D reconstruction, world models and VLMs.
• Experience working with synthetic data pipelines and robotics simulation infrastructure (e.g. Isaac Sim, Gazebo, Blender, Unity).
• Extensive experience with Python and common ML frameworks like PyTorch.
• Should be comfortable taking ownership of tasks with light supervision.
• Must have excellent problem-solving skills.
• Legally authorized to work in the United States.

USA, California, Santa Clara

Intelligent machines powered by artificial intelligence—computers that can learn, reason, and interact with people—are transforming every industry. GPU-accelerated deep learning provides the foundation for machines to perceive, reason, and solve complex problems. NVIDIA GPUs run deep learning algorithms that simulate aspects of human intelligence, acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world.

We are seeking an exceptional Senior Perception Engineer to help design and productize NVIDIA’s next-generation autonomous driving perception stack. You will work on the core 3D obstacle perception pipeline, contribute to architecture and algorithm design, and remain deeply hands-on with implementation, including modern transformer-based, multi-modal, and vision-language techniques where they add real value.

What you’ll be doing: - Develop and improve the technical design, architecture, and roadmap for 3D obstacle perception to support end-to-end autonomous driving functionalities, leveraging state-of-the-art CNN and transformer-based architectures where appropriate. - Design and implement advanced 3D perception models using multi-camera inputs and/or multi-sensor fusion (camera, radar, lidar) for obstacle detection and tracking, including opportunities to explore BEV and transformer-based 3D perception. - Build efficient, production-grade deep learning models: define objectives with the team, select and prototype architectures, run experiments, and follow best practices for training and evaluation, using techniques such as large-scale pretraining, distillation, and parameter-efficient fine-tuning (e.g., LoRA). - Help define and maintain KPI frameworks to quantify perception performance; analyze large-scale real and synthetic datasets to identify failure modes and systematically improve accuracy, robustness, and efficiency, incorporating approaches like self-supervised and representation learning when beneficial. - Contribute to the data strategy for perception: specify data and labeling requirements, help prioritize data collection and annotation, and collaborate with data and ground-truth teams, including model-assisted workflows (e.g., active learning, auto-labeling, vision-language models (VLMs)) and model-in-the-loop tooling. - Collaborate with safety, systems, and software teams to ensure perception solutions meet product requirements for safety, latency, resource usage, and software robustness, and are ready for deployment at scale.

What we need to see: - PhD with 4+ years, MS with 6+ years, or BS (or equivalent experience) with 8+ years of relevant experience in Computer Science, Computer Engineering, or a related technical field. - Hands-on experience developing deep learning–based perception or closely related systems for complex real-world problems, with strong proficiency in frameworks such as PyTorch and a track record of taking models from prototype to production. - Proven experience in data-driven development, including close collaboration with data, labeling, and ground-truth teams on data strategy, labeling quality, and iterative model improvement. - Strong programming skills in Python and/or C++, with experience building reliable, high-performance, production-quality software. - Excellent communication and collaboration skills, with the ability to work effectively across multidisciplinary teams.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

This posting is for an existing vacancy.