Mission Summary:

Motional’s onboard autonomous driving system team works at the intersection of software engineering, machine learning, sensors, and hardware compute platforms to evolve Motional’s next-generation on-board autonomous driving system. As part of this team, the High Performance Compute Platform team is responsible for Motional’s current and next-generation onboard autonomous driving system. If you are a software engineer and love the idea of working on embedded AI hardware and software compute systems to create the next generation of autonomous vehicles, we would love to talk with you. We are hiring in a range of levels, from graduate engineers to Staff engineers.

What You'll Be Doing:

• Design and develop infrastructure software on various hardware platforms for applications such as vision processing, radar systems, safety monitoring, etc., to be run on self-driving vehicles.
• Design test harnesses for embedded software components and full systems
• Provide technical mentorship to engineers.
• Proactively work with cross-functional engineering teams to solve complex and interesting problems.
  
  

What We're Looking For:

• Experience with creating detailed requirements from use cases.
• Ability to lead a technical initiative, including breaking down work and guiding other engineers through execution.
• Experience writing software for embedded platforms in C and C++.
• Experience with Test-Driven Development (TDD).
• Experience working on embedded Linux / RTOSs.
• Experience working with networks (Ethernet, CAN etc.) and the common networking protocols.
• Experience with debugging on embedded platforms.
• Experience writing software in Python and experience doing automation with shell scripting.
• Experience working with ARM Cortex MCUs or Microprocessors.
  
  

Bonus Points (not required):

• Experience working with large data pipelines, and platforms that require deterministic execution.
• Experience using inter-system communication protocols such as I2C and SPI
• Experience deploying Machine Learning models.
• Experience working with GPUs.
• Experience working directly with the Linux kernel or Device Drivers.
• Experience with Simulation and Code Generation, and knowing when their use is appropriate.
• Experience working with Bazel.
• Experience integrating various sensors, including Cameras, IMUs, Radars, LIDARs.
• Experience with PyTorch, TensorFlow, ONNX, and/or other ML frameworks. 
  
  

We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.

Mission Summary:

As a seasoned expert in Perception Capabilities, you'll field cutting-edge software products and solutions using state-of-the-art computer vision and deep learning. Your breadth of experience spans critical problem areas like detection, classification, segmentation, and tracking, along with essential supporting functions such as data engines, labeling policies, training pipelines, model optimization, simulation, and testing. You're driven by seeing your work significantly impact the product, taking initiative and owning outcomes.

You're eager to apply these skills to the perception stack of self-driving vehicles. You understand the unique challenges of safety-critical, open-world applications and are committed to ensuring engineering excellence and rigorous evaluation.

You'll devise creative solutions to complex problems, collaborating with interdisciplinary, capability-focused teams across the organization to design, implement, and validate end-to-end solutions.

What you’ll be doing:

• Lead the development and implementation of solutions that span across perception components and directly interface with downstream modules in the autonomy system.
• Analyze the performance of the perception subsystem to proactively identify potential limitations with respect to a set of system-level capabilities. Document potential hazards and lead the cross-team efforts to eliminate or mitigate them.
• Collaborate on innovative solutions to address “long tail” challenges. For example, developing techniques for synthetic data generation, advanced data mining, or leveraging language embeddings in our onboard models.
• Depending on your background and interests, you may also help optimize and deploy models to the vehicle, ensuring they operate within the constraints of our onboard hardware and meet our functional requirements and interface specifications.
• Interface with systems and safety engineers, test engineers, and data analysts to ensure appropriate requirements, test coverage, and performance metrics

What We’re Looking for:

• Master's or Ph.D. in Machine Learning, Computer Science, Robotics, or a related field; or equivalent industry experience
• Strong leadership skills in executing large, complex technical initiatives
• Track record of successful interdisciplinary work and product-focused engineering
• Broad understanding of Deep Learning algorithms, architectures, and applications
• Experience designing, training, and analyzing neural networks for applications relevant to perception
• Fluency in Python, including common libraries for deep learning (PyTorch), scientific computing, and data analysis and visualization
• Advanced knowledge of software engineering principles, including software design, source control management, build processes, code reviews, and  testing methods 
• Excellent communication and interpersonal skills
• Experience mentoring and leading others

Bonus Points:

• Experience shipping a “real” product and balancing ongoing support with next-generation innovation
• Experience developing safety-critical products or components
• Publications in relevant conferences (CVPR, ICML, NeurIPS, etc.)
• Strong programming skills in C++ and/or CUDA programming
• Experience with TensorRT and model quantization

You’re an engineer who is excited to work on cutting-edge software products and solutions using state-of-the-art computer vision and deep learning. You have a solid foundation in areas like detection, classification, segmentation, or tracking—whether through previous roles, internships, or research—and you’re eager to apply those skills in an impactful, production-focused environment.

You’re curious, motivated, and ready to learn from experienced teammates. You enjoy solving challenging technical problems, asking thoughtful questions, and collaborating with others to build high-quality software.

You’re excited about contributing to the perception stack for self-driving vehicles and learning what it means to build technology for safety-critical, open-world applications.

What you’ll be doing:

• Contribute to the design, development, and improvement of perception components that support downstream modules within the autonomy system.
• Help analyze perception system performance to identify areas for improvement and participate in efforts to address them.
• Work with teammates to explore creative approaches to “long-tail” challenges—for example, experimenting with synthetic data, data mining techniques, or new model architectures.
• Depending on your background and interests, you may also help optimize and deploy models to the vehicle, ensuring they operate within the constraints of our onboard hardware and meet our functional requirements and interface specifications.
• Interface with systems and safety engineers, test engineers, and data analysts to ensure appropriate requirements, test coverage, and performance metrics

What We’re Looking for:

• Master's or Ph.D. in Machine Learning, Computer Science, Robotics, or a related field; or equivalent industry experience
• Solid understanding of fundamental deep learning concepts and computer vision techniques
• Experience building, training, or evaluating neural networks
• Proficiency in Python and familiarity with libraries like PyTorch or similar
• Exposure to software engineering fundamentals—version control, code reviews, testing, and collaborative development
• Clear communication skills and willingness to ask questions, share ideas, and work with others

Bonus Points:

• Previous experience with sensor fusion and/or previous exposure to the AV industry
• Experience shipping a “real” product and balancing ongoing support with next-generation innovation
• Exposure to safety-critical products or components
• Publications in relevant conferences (CVPR, ICML, NeurIPS, etc.)
• Strong programming skills in C++ and/or CUDA programming
• Experience with TensorRT and model quantization

Mission Summary:

We are seeking an experienced and visionary Principle Level Tech Lead Manager to build and lead our new Machine Learning (ML) Acceleration team. This pivotal role will drive the strategy, development, and execution of initiatives aimed at significantly accelerating ML model training. The ultimate goal is to drastically reduce the development cycle for new ML models and enable rapid hot-patching for issues within our deployed autonomous vehicle services.

You will be a hands-on leader, blending deep technical expertise in ML systems and performance optimization with strong leadership and people management skills. You will recruit, mentor, and grow a high-performing team of engineers, fostering a culture of innovation, collaboration, and continuous improvement.

What you'll be doing:

• Team Leadership & Management:
• Build, lead, and manage a high-performing team of ML and infra engineers focused on acceleration.
• Provide technical guidance, mentorship, and career development opportunities to team members.
• Foster a collaborative and inclusive team environment.
• Define team goals, priorities, and roadmap in alignment with company objectives.
  
  
• Technical Strategy & Execution:
• Define the technical vision and strategy for ML acceleration across the organization.
• Identify and evaluate cutting-edge technologies and methodologies for speeding up ML training, including but not limited to data pipeline optimization, large scale distributed training, data loader optimization, hardware acceleration, and model optimization techniques.
• Design, develop, and implement scalable and efficient ML acceleration solutions.
  
  
• Cross-functional Collaboration:
• Collaborate closely with ML research, ML Training platform, and product teams to understand their needs and integrate acceleration solutions seamlessly.
• Communicate complex technical concepts and strategies to both technical and non-technical stakeholders.
• Act as a technical expert and advocate for ML acceleration initiatives across the company.
  
  
• Impact & Measurement:
• Regularly measure and report on the impact of acceleration efforts.
• Continuously seek opportunities for further optimization and innovation.
  
  

What we're looking for:

• Experience:
• Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience
• 8+ years of experience in software engineering, with at least 5+ years focused on Machine Learning systems, and model performance optimization.
• 3+ years of experience in a technical lead or management role, with a proven track record of building and leading high-performing teams.
• Extensive experience with large-scale ML model training and deployment, ideally in a production environment.
• Strong understanding of distributed systems and cloud computing platforms (e.g., AWS, GCP, Azure).
  
  
• Technical Skills:
• Deep expertise in ML frameworks such as PyTorch or JAX.
• Proficiency in performance profiling and optimization techniques for Deep Neural Networks.
• Strong programming skills in Python; C++ experience is a plus.
• Knowledge of MLOps principles and practices.
  
  
• Leadership Skills:
• Exceptional leadership, communication, and interpersonal skills.
• Ability to attract, hire, and retain top engineering talent.
• Proven ability to drive complex technical projects from conception to completion.
• Strong problem-solving skills and a proactive, results-oriented mindset.
• Ability to thrive in a fast-paced, dynamic environment.

Mission Summary:

We are seeking an experienced and visionary Principle Level Tech Lead Manager to build and lead our new Machine Learning (ML) Acceleration team. This pivotal role will drive the strategy, development, and execution of initiatives aimed at significantly accelerating ML model training. The ultimate goal is to drastically reduce the development cycle for new ML models and enable rapid hot-patching for issues within our deployed autonomous vehicle services.

You will be a hands-on leader, blending deep technical expertise in ML systems and performance optimization with strong leadership and people management skills. You will recruit, mentor, and grow a high-performing team of engineers, fostering a culture of innovation, collaboration, and continuous improvement.

What you'll be doing:

• Team Leadership & Management:
• Build, lead, and manage a high-performing team of ML and infra engineers focused on acceleration.
• Provide technical guidance, mentorship, and career development opportunities to team members.
• Foster a collaborative and inclusive team environment.
• Define team goals, priorities, and roadmap in alignment with company objectives.
  
  
• Technical Strategy & Execution:
• Define the technical vision and strategy for ML acceleration across the organization.
• Identify and evaluate cutting-edge technologies and methodologies for speeding up ML training, including but not limited to data pipeline optimization, large scale distributed training, data loader optimization, hardware acceleration, and model optimization techniques.
• Design, develop, and implement scalable and efficient ML acceleration solutions.
  
  
• Cross-functional Collaboration:
• Collaborate closely with ML research, ML Training platform, and product teams to understand their needs and integrate acceleration solutions seamlessly.
• Communicate complex technical concepts and strategies to both technical and non-technical stakeholders.
• Act as a technical expert and advocate for ML acceleration initiatives across the company.
  
  
• Impact & Measurement:
• Regularly measure and report on the impact of acceleration efforts.
• Continuously seek opportunities for further optimization and innovation.
  
  

What we're looking for:

• Experience:
• Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience
• 8+ years of experience in software engineering, with at least 5+ years focused on Machine Learning systems and model performance optimization.
• 3+ years of experience in a technical lead or management role, with a proven track record of building and leading high-performing teams.
• Extensive experience with large-scale ML model training and deployment, ideally in a production environment.
• Strong understanding of distributed systems and cloud computing platforms (e.g., AWS, GCP, Azure).
  
  
• Technical Skills:
• Deep expertise in ML frameworks such as PyTorch or JAX.
• Proficiency in performance profiling and optimization techniques for Deep Neural Networks.
• Strong programming skills in Python; C++ experience is a plus.
• Knowledge of MLOps principles and practices.
  
  
• Leadership Skills:
• Exceptional leadership, communication, and interpersonal skills.
• Ability to attract, hire, and retain top engineering talent.
• Proven ability to drive complex technical projects from conception to completion.
• Strong problem-solving skills and a proactive, results-oriented mindset.
• Ability to thrive in a fast-paced, dynamic environment.

Mission Summary:

At Motional, we're transforming how autonomous vehicles discover critical intelligence hidden within petabytes of multimodal sensor data. Our next-generation autonomous driving stack depends on finding the rare edge cases, long-tail scenarios, and model errors that matter most. Omnitag, our ML-powered multimodal data mining framework, is the engine that powers this discovery.

As a Senior Machine Learning Engineer on the Data Mining team, your mission is to build the "Brain" of this engine: designing massive multimodal Teacher models that understand the world, and distilling them into hyper-efficient Student models that can scour exabytes of data in near real-time. You will work at the intersection of large-scale representation learning, retrieval optimization, and reasoning systems. Your work will directly influence how we compress knowledge into efficient encoders for fast search, and how we apply reinforcement learning to optimize data discovery workflows and intelligent querying. By building smarter mining tools, you will accelerate the entire model improvement lifecycle for teams working on post-training analysis, error diagnosis, and dataset curation.

What You'll Do:

• Architect and Train Distilled Models: Design and implement teacher-student model frameworks for multimodal sensor data. Develop training pipelines for knowledge distillation. Ensure student models maintain high accuracy while drastically reducing inference latency and memory footprint.
• Reinforcement Learning for Data Discover: Build RL-based policy learning and reasoning systems for autonomous driving applications. Implement and scale RL training workflows (e.g., PPO, DQN, actor-critic methods) for simulation and real-world interaction. Explore reward shaping, environment modeling, and multi-agent RL where applicable.
• Optimize Model Deployment for Real-Time Inference: Collaborate with backend engineers to deploy distilled and RL models into production. Optimize for latency, throughput, and hardware efficiency across GPU/CPU clusters. Implement model versioning, A/B testing, and monitoring for performance regressions.
• Research and Integrate Agentic Systems: Explore and prototype agentic workflows for autonomous reasoning, chain-of-thought prompting, and goal-directed behavior. Integrate such systems into our broader autonomy stack as experimental or production components.
• Drive Production Reliability: Establish patterns for graceful degradation, fault tolerance, and cost optimization. Operate Omnitag as a mission-critical data platform serving the entire ML organization, with a focus on reliability, debuggability, and operational excellence.
• Mentor and Collaborate: Work closely with ML scientists, data engineers, and autonomy teams to translate research advances into scalable engineering solutions. Guide junior engineers in best practices for model training, evaluation, and deployment.

What We're Looking For:

• BS in Computer Science, Machine Learning, or related field, or equivalent professional experience.
• 6+ years of hands-on experience in machine learning engineering, with a focus on model post training, optimization, and deployment.
• Strong experience with model distillation or teacher-student training - practical knowledge of loss functions, training strategies, and evaluation of compressed models.
• Proven experience with reinforcement learning in production or research settings: policy optimization, reward design, simulation environments, and RL-based reasoning.
• Expert-level proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX).
• Strong software engineering fundamentals: testing, CI/CD, containerization, and system design.
• Experience deploying ML models in cloud environments (AWS, GCP, or Azure) and optimizing for inference.
• Demonstrated ability to ship production-grade ML systems and mentor team members.
• Demonstrated track record of shipping robust, well-tested, production-grade systems and mentoring junior engineers

Bonus Points (Nice-to-Haves):

• MS/PhD in Computer Science, Machine Learning, or related field.
• Experience with agentic systems, autonomous reasoning, chain-of-thought models, or LLM-based planning.
• Background in autonomous driving, robotics, or real-time decision-making systems.
• Familiarity with multimodal learning, sensor fusion, or embodied AI.
• Experience building active learning loops, using the model to find the data that breaks the model.
• Experience with ML-based data mining, active learning, or contrastive learning.
• Knowledge of model serving tools (TF Serving, Triton, TorchServe) and MLOps platforms.
• Publications or open-source contributions in RL, distillation, or efficient ML.
  
  

We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.

On our Behaviors team (Prediction and ML Planner), you will have the opportunity to work with world-class ML engineers, whose mission is to make self-driving vehicles a reality and to create a positive social impact. The Behaviors team develops ML models that learn how different agents navigate complex real-world traffic scenarios. We leverage these models to set the behavior of our self-driving vehicle, and predict the behavior of other agents such as vehicles and vulnerable road users. 

We are looking for proven leaders and technical experts who are passionate about Level 4 autonomous driving technology, excited by intellectual challenges, and interested in pursuing career growth with a fast-growing company.

What You’ll Be Doing:

• Define and execute motion planning and prediction projects that improve our self-driving vehicles’ capability to safely, comfortably and legally navigate complex traffic scenarios
• Lead, manage and grow a team of engineers
• Design and lead the implementation of behavior models that leverage the latest advancements in machine learning, generative AI and reinforcement learning
• Productionize and deploy solutions onto autonomous vehicle fleets
• Collaborate with perception, simulation, data platform and integration teams to validate and enhance your products’ on-road performance
• Communicate strategies, progress and challenges to executive leadership

What We’re Looking for:

• Masters or Ph.D. in Computer Science or a related technical field; or equivalent industry experience
• Proven leadership skills at executing large, complex technical initiatives
• Extensive experience managing and leading engineers
• Experience with deep learning frameworks such as TensorFlow or PyTorch
• Fluency in Python, including standard scientific computing libraries
• Proven track record of designing, developing and deploying ML solutions for autonomous vehicles or robotics
• Advanced knowledge of software engineering principles including software design, source control management, build processes, code reviews, testing methods 
• Excellent communication and interpersonal skills

Bonus Points:

• Experience with embedded systems and real-time optimization, especially in the autonomous driving industry
• Experience with state of the art generative AI, and/or reinforcement learning, paradigms
• Proven track record of publications in relevant conferences (CVPR, ICML, NeurIPS, ICCV, ICL, etc.)
• Strong programming skills in C++ and/or CUDA programming

On Behaviors, you'll have the opportunity to work with world-class ML engineers and research scientists to make self-driving vehicles a reality and create positive social impact. Our team works on the tech stack responsible for understanding highly complex driving scenes and generating safe, comfortable driving trajectories for our robotaxi using the latest deep neural networks. We are looking for engineers who are passionate about Level 5 autonomous driving, excited by intellectual challenges, and interested in pursuing career growth with a fast growing company.

What You’ll Be Doing:

You will be directly responsible for training, evaluation, and deployment of our ML-based scene understanding, behavior prediction, and planning models. Day to day responsibilities include:

• Designing and executing high value experiments based on collaborative input from other machine learning engineers
• Prototyping and implementing continuously improving metrics to evaluate the performance of our behavioral models across many desired scenarios and robotaxi capabilities
• Timely release of major model updates, including analysis of both off-line and on-road evaluation data
• Staying up to date with the latest trends in our fast moving industry, and proposing new architectures and network designs based on published literature
• Maintaining a high quality training and evaluation code-base, including portions of our training stack dedicated to dataset generation and evaluation

What We’re Looking For:

• In-depth understanding of common Machine Learning and Deep Learning algorithms
• Experience designing, training, and analyzing neural networks for at least one of the following applications: motion planning, object detection, sensor fusion, motion prediction, and/or multi-object tracking
• Strong track record of tackling less well-defined problems, and executing efficiently to deliver the successful outcome
• Advanced knowledge of software engineering principles including software design, source control management, build processes, code reviews, and  testing methods
• Experience with PyTorch or other python-based deep learning frameworks
• Experience working with large data sets and deriving insights from data
• Experience mentoring and collaborating with others

Education
Masters or PhD in Machine Learning, Computer Science, Applied Mathematics, Statistics, Physics or a related field; or equivalent industry experience

Bonus Points

• Publications in relevant conferences (CVPR, ICML, NeurIPS, ICCV, ICL, etc.)
• PhD in machine learning, computer vision, or robotics vision
• Experience working on autonomous vehicles or related fields
• Experience in deploying models into real-world environments
• Strong programming skills in C++ and/or CUDA programming
• This opportunity can support remote work within the United States, with occasional travel.

Working Conditions

While performing the duties of this job, the employee is frequently required to convey and detect communication

The employee occasionally required to remain stationary at times for up to 50% of working time, move in designated working areas; & operate and use office equipment

The employee may occasionally move up to 50 pounds

Motional’s global headquarters are located at 100 Northern Avenue in Boston, MA. Nestled in the bustling Seaport district with sweeping views of Boston Harbor and downtown Boston, the office is located close to major transit lines and a quick walk to various restaurants and popular attractions.

Mission Summary:

Motional’s CORE team is responsible for our vehicle’s Compute and Onboard Runtime Environment. We are creating a world leading AI compute platform for autonomous vehicles. This is the system that executes the software and neural networks that make our vehicles autonomous. 

The Next-Gen Technologies team is part of CORE. We work at the intersection of software engineering, machine learning, sensors, and hardware compute platforms to evolve Motional’s on-board vehicle architecture. If you are a software engineer and love the idea of working on embedded AI hardware and software systems to create the next generation of autonomous vehicles, we would love to talk with you. 

What You’ll Be Doing:

As a senior engineer in the Next-Gen Technologies team, you will help us improve the compute performance of our current generation and next-generation autonomous driving systems through participating in full lifecycle development from idea to proofs-of-concept to production. 

Specifically, you will:

• Focus deeply on ML model deployment, integration of multiple ML models, and ML model optimization on embedded compute platforms.
• Dive deep into the full ML software stack. Analyze ML workload performance on a variety of hardware processors, optimize ML models, improve ML software, and help us continually improve our stack through the application of efficient and effective ML approaches. 
• Design, develop, test, integrate, and optimize software and tools on a variety of ML compute architectures.
• Collaborate with deep learning experts in perception, prediction, and other autonomous driving application areas to enable algorithms on GPU, NPU, and other ML accelerator architectures.
• Optimize the utilization of GPU/NPU resources and sharing of GPU/NPU access across multiple programs running on the same system.
• Lead designs to determine the needs of the system and how to best meet those needs through continually improving our ML software stack.
• Advise peers and management on technical matters.

What We’re Looking For:

• Experience with machine learning accelerators, including GPUs, NPUs, TPUs, and their programming environments, including CUDA, TensorRT, or similar technologies.
• Strong experience with modern C++ development in a Linux environment.
• Experience with parallel and high-performance computing.
• Comfortable with experimentation and evaluating different options as we work towards finding solutions that work. 
• A degree in Software Engineering, Computer Science, Electrical or Electronic Engineering, or similar technical field of study, or you have equivalent knowledge gained through your practical experience.

Preferred, but not required:

• Experience with PyTorch, TensorFlow, ONNX, and/or other ML frameworks. 
• Experience with embedded systems development for ARM-based system-on-chip architectures.
• Experience working in a MLOps or DevOps environment.
• Passion for self-driving technology and its potential for positive impact on the world.
  
  

This role is hybrid from our Boston office. It requires two in-office days each week, ideally Tuesday and Thursday.

On Behaviors, you'll have the opportunity to work with world-class ML engineers and research scientists to make self-driving vehicles a reality and create positive social impact. Our team works on the tech stack responsible for understanding highly complex driving scenes and generating safe, comfortable driving trajectories for our robotaxi using the latest deep neural networks. We are looking for engineers who are passionate about Level 5 autonomous driving, excited by intellectual challenges, and interested in pursuing career growth with a fast growing company.

What You’ll Be Doing:

You will be directly responsible for training, evaluation, and deployment of our ML-based scene understanding, behavior prediction, and planning models. Day to day responsibilities include:

• Designing and executing high value experiments based on collaborative input from other machine learning engineers
• Prototyping and implementing continuously improving metrics to evaluate the performance of our behavioral models across many desired scenarios and robotaxi capabilities
• Timely release of major model updates, including analysis of both off-line and on-road evaluation data
• Staying up to date with the latest trends in our fast moving industry, and proposing new architectures and network designs based on published literature
• Maintaining a high quality training and evaluation code-base, including portions of our training stack dedicated to dataset generation and evaluation

What We’re Looking For:

• In-depth understanding of common Machine Learning and Deep Learning algorithms
• Experience designing, training, and analyzing neural networks for at least one of the following applications: motion planning, object detection, sensor fusion, motion prediction, and/or multi-object tracking
• Strong track record of tackling less well-defined problems, and executing efficiently to deliver the successful outcome
• Advanced knowledge of software engineering principles including software design, source control management, build processes, code reviews, and  testing methods
• Experience with PyTorch or other python-based deep learning frameworks
• Experience working with large data sets and deriving insights from data
• Experience mentoring and collaborating with others

Education
Masters or PhD in Machine Learning, Computer Science, Applied Mathematics, Statistics, Physics or a related field; or equivalent industry experience

Bonus Points

• Publications in relevant conferences (CVPR, ICML, NeurIPS, ICCV, ICL, etc.)
• PhD in machine learning, computer vision, or robotics vision
• Experience working on autonomous vehicles or related fields
• Experience in deploying models into real-world environments
• Strong programming skills in C++ and/or CUDA programming
• This opportunity can support remote work within the United States, with occasional travel.

Working Conditions

While performing the duties of this job, the employee is frequently required to convey and detect communication

The employee occasionally required to remain stationary at times for up to 50% of working time, move in designated working areas; & operate and use office equipment

The employee may occasionally move up to 50 pounds

Senior Vision AI Engineer 
(Cognitive Vision and Industrial AI)

Location: Mid-Atlantic Region
Company: Linque
Reports to: Head of Vision AI

About Proconex

Proconex is a trusted leader in industrial automation and process control solutions, proudly serving the industry for over 75 years. With a rich legacy of delivering high-performance systems and equipment to process industries—including oil & gas, chemicals, power, and life sciences—we are now entering an exciting new chapter.

We are  building on a solid foundation of over 10 years of successful deployments with our next generation of software products. Our software solutions are designed to empower industrial operators with operational analytics, enabling smarter, more efficient, and more reliable operations. This is a unique opportunity to be part of a growth-focused team that is taking proven technology to the next level.

About the Role

Linque is expanding its Vision AI and Cognitive Automation platform focused on applying real-time computer vision and AI to industrial, biopharmaceutical, and process manufacturing environments. We are seeking a Senior Vision AI Engineer to help lead the development, deployment, and customer-facing application of advanced vision AI solutions. This role sits at the intersection of deep technical execution, platform development, and real-world industrial use cases.

Key Responsibilities

• Design, develop, and deploy production-grade computer vision and machine learning models
• Build optimized end-to-end vision pipelines for real-time and near-real-time applications
• Translate complex industrial problems into scalable AI architecture
• Collaborate cross-functionally with product, engineering, and commercial teams
• Participate in technical customer discussions, pilots, and evaluations
• Support prototypes through pilot and production transitions
• Mentor junior engineers and contribute to technical best practices

Required Qualifications

• 5+ years’ experience in computer vision and machine learning
• Strong hands-on experience deploying AI systems in production
• Proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow, Keras)
• Deep knowledge of Video / Image processing tools (e.g. Mask R-CNN, ResNet, U-Net)
• Knowledge of object and anomaly detection (Autoencoders, FastFlow, Transformers)
• Tunning experience for CNNs and Vision Models (e.g., MLFlow, NVIDIA TAO, MMD, MMS)
• Mastery of model interchange and GPU acceleration (e.g. ONNX, CUDA, cuDNN)
• Experience working with image/video pipelines, container orchestration (local and cloud)
• Understanding of the full ML / AI lifecycle

Preferred Qualifications

• Experience with real-time vision systems
• Background in industrial automation or regulated environments
• Experience with edge or cloud deployment
• Ability to communicate complex technical topics clearly

Why Join Linque

• Apply AI to real industrial problems with measurable impact
• Collaborate with experienced AI and industrial leaders
• Influence the evolution of next-generation Vision AI platforms
• Flexible, growth-oriented environment

Apply today to learn more about this exciting new opportunity at Proconex, the exclusive Emerson Impact Partner for the Mid-Atlantic region!

What we are looking for

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 Software Engineer II to join the Control Simulation team and help transform how we validate and improve the safety and performance of the Aurora Driver.

In this role, you will operate at the intersection of Machine Learning, Software Engineering, Data Science, and Vehicle Dynamics. You will contribute to the development of our next-generation data driven vehicle simulator, build data pipelines that source critical scenarios from our fleet and generate simulations from logs, and analyze data to prove the safety of our motion control software.

This is a high-impact role for an engineer who enjoys a mix of model development, infrastructure building, and data analysis.

In This Role You Will:

• Develop Vehicle Models: Help design and implement our next-generation differentiable vehicle dynamics simulator for controls V&V.
• Build Simulation Pipelines: Design and maintain the software pipelines required to generate "Sim-from-Log" scenarios. You will ensure that high-value on-road events are systematically converted into reproducible simulation tests.
• Implement Control Scenario Taxonomies & Curate Data: Build the data structures and algorithms to categorize complex control scenarios (e.g., maneuvers, environments) and use this framework to source balanced datasets from on-road logs, ensuring comprehensive ODD coverage for model training.

Required Qualifications:

• BS or MS in Computer Science, Robotics, Data Science, or a related engineering field.
• 2+ years of software engineering experience with a focus on data-intensive applications or machine learning.
• Strong proficiency in Python (including libraries like Pandas, NumPy, Scikit-learn).
• Hands-on experience with PyTorch or similar machine learning frameworks.
• Experience working with large datasets, SQL, and data processing pipelines.
• Strong analytical skills with the ability to translate complex data into actionable engineering insights.
• Background or interest in Control Theory or Vehicle Dynamics (understanding of kinematics, kinetics, and actuation).

Desirable Qualifications:

• Experience with machine learning or system identification for physics based-models.
• Familiarity with V&V methodologies, simulation frameworks, or log analysis tools.
• Experience building data visualization tools or dashboards to track software quality and coverage.
• Proficiency in C++ (necessary for integrating with on-vehicle or production codebases).

The base salary range for this position is $126,000-$181,000 per year.  Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits.

 #LI-KW1

#Associate

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 are seeking a ML Engineering TL to join the Behavior Planning Team. This is a high-impact role where you will sit at the frontier of autonomous vehicle technology. You won't just be applying AI and ML methods; you will be advancing the state-of-the-art for how a self-driving system reasons about the world, interacts with humans on the road, and masters complex, high-dimensional decision-making.

In this role, you will

• Define the architecture of our onboard planning models: Develop and deploy large-scale models trained with Imitation Learning and Reinforcement Learning that enable the Aurora Driver to navigate complex environments with human-like fluidity and superhuman safety.
• Build our next-generation simulation engine: Architect cutting-edge offboard foundation models that power our simulation engine, creating realistic "world models" to test the Aurora Driver against an infinite variety of edge cases.
• Revolutionize evaluation: Develop powerful offboard critic models that can evaluate driving behavior at scale, identifying subtle nuances in comfort, progress, and safety that traditional heuristics miss.
• Bridge research and production: Reach new frontiers of autonomous driving technology by pushing forward the state-of-the-art, but also deploy your models on real production vehicles that drive on public roads and must meet the highest standards of safety. 
• Mentor and lead: Serve as a technical lead, guiding junior engineers and shaping the long-term roadmap for ML-based planning at Aurora, including the onboard and off-board ecosystem that is needed to support it.

Required Qualifications

• MS or PhD in Robotics, Machine Learning, Computer Science, or a related quantitative field, or equivalent practical experience.
• 8 + years of experience developing state-of-the-art ML models, either in a research or production setting.
• Hands-on experience working on Imitation Learning or Reinforcement Learning applied to physical or simulated agents.
• Experience training large models on massive datasets using distributed computing.
• Fluency in Python, with a focus on writing high-performance, maintainable code.
• Deep experience with PyTorch (preferred) or another modern ML framework, and a mastery of modern ML architectures including Transformers and Diffusion Models.

Desirable Qualifications

• A track record of publications in top-tier ML conferences (NeurIPS, ICML, CoRL, CVPR, AAAI).
• Experience deploying complex ML systems in production environments.
• Experience in developing generative models or neural simulators for synthetic data generation.
• Experience leading small or large teams to execute highly technical projects.

The base salary range for this position is $171K - $247K per year. Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits.

#LI-JL261

#Mid-Senior 

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 Software Engineer to join Aurora’s Behavior Planning ML Platform team.  Our team is responsible for building both the offline pipelines to train and evaluate models and the infrastructure to efficiently run these models onboard the vehicle. On the offboard side, we build and support  the large scale distributed pipelines that model developers rely on to source data at scale, train, and evaluate machine learning models. On the onboard side, we build and maintain the on-vehicle infrastructure required to deploy these models and run inference in a soft real-time system.

In this role, you will

• Develop large scale pipelines for data extraction, model training and model evaluation
• Build and optimize onboard ML infrastructure used to deploy models and run inference onboard the vehicle
• Collaborate closely with motion planning, systems engineering, and other autonomy groups to define and develop critical ML workflow requirements.

Required Qualifications

• BS or higher degree in Computer Science/Engineering or related fields. > 6 months of experience
• Strong programming skills in C++ or Python, ideally both
• Experience with machine learning frameworks (PyTorch or TensorFlow)
• Solid foundation in computer science fundamentals - especially operating system concepts including concurrency, memory management and process scheduling.

Desirable Qualifications (this section is optional)

• Experience with GPU programming and Nvidia profiling tools - CUDA, NSight Systems, Nsight Compute
• Experience working in cloud compute (AWS, Azure, GCP) ideally with batch processing or other large-scale workflow management platforms. 
• Experience profiling and optimizing software on Linux

The base salary range for this position is $126,000 - $181,000 per year.  Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits.

#LI-JL261

#Mid-Senior 

About the Role:

As a Senior Data Scientist at Perpay, you will be a critical player in the day-to-day success of the business, supporting new and existing product initiatives through strong analytical skills and machine learning expertise. In addition, you will be responsible for helping shape the future of the data science team by developing processes and systems that scale with our rapidly growing business. This is an exciting opportunity to make a positive impact on the execution of Perpay’s mission and the lives of our customers. We are looking for someone who is passionate about all aspects of data science: from machine learning and exploratory data analysis to communication of results and real-time deployments. This crucial role will sit on our data science team and report to the Data Science Manager. If you’re looking for a collaborative team that you can bounce ideas off of and learn from, this is where you belong. We are about being curious, setting the standard and building good habits at Perpay.

Our greatest strength is our people and we’d love for you to be one of them!

Responsibilities:

• Drive the end-to-end completion of data science initiatives, collaborating with stakeholders from ideation through execution, ensuring projects deliver strong impact to our customer’s financial lives and the health of the business
• Proactively identify opportunities for the data science team to improve and expand Perpay’s business model using techniques from exploratory data analysis to machine learning models, leveraging subject matter expertise of Perpay’s business model
• Support the growth of the business by delivering scalable models and algorithms while maintaining and troubleshooting existing resources
• Deploy and maintain real-time model inference resources and infrastructure
• Deploy and maintain machine learning pipelines including batch processing and continuous training architecture
• Contribute to the cross-discipline adoption and responsible use of AI/LLM models and services at Perpay 
• Present results and analyses to the a wide range of audiences: from Perpay's leadership team to non-technical peers
• Contribute to defining standards and best practices concerning workflow and adoption of new technologies within the Data Science team
• Act as an informal mentor peers

What You’ll Bring:

• 5+ years of experience* and expertise applying machine learning techniques in industry
• 5+ years of experience* and expertise in producing data analysis, exploratory data analysis and data visualization in industry
• 5+ years of experience* and expertise in developing, deploying, maintaining real-time software (e.g. models exposed as APIs)
• 5+ years of experience* and expertise in Cloud compute infrastructure and best practices, including familiarity with tools such as terraform and Cloud Formation
• Bachelor's degree or higher in a quantitative/technical field (Mathematics, Statistics, Engineering, Chemistry, Physics)
• Excellent communication skills, across a range of audiences from technical to non-technical
• Strong business acumen, demonstrated through subject matter expertise in at least one industry
• Capable of managing projects “end to end” including managing project scope, timelines and workloads
• Advanced proficiency in Python and standard data science stack (e.g. scikit-learn, pandas, numpy, matplotlib, etc.)
• Team player: willingness and ability to establish strong working relationships not just within the data science team itself, but across the organization

*Internships not included

Nice to have:

• Expertise in multiple advanced machine learning methodologies: e.g. deep learning, probabilistic programming, mathematical optimization, etc.
• Deep familiarity in multiple advanced machine learning frameworks: e.g. tensorflow, pytorch, pymc, etc.
• Experience with scalable compute frameworks such as Spark or Polars
• Experience with deployment frameworks such as Kubernetes