Latitude AI (lat.ai) develops automated driving technologies, including L3, for Ford vehicles at scale. We’re driven by the opportunity to reimagine what it’s like to drive and make travel safer, less stressful, and more enjoyable for everyone.

When you join the Latitude team, you’ll work alongside leading experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, systems and safety engineering – all dedicated to making a real, positive impact on the driving experience for millions of people. 

As a Ford Motor Company subsidiary, we operate independently to develop automated driving technology at the speed of a technology startup. Latitude is headquartered in Pittsburgh with engineering centers in Dearborn, Mich., and Palo Alto, Calif.

Meet the team:

The hardware sensing team is responsible for the benchmarking, characterizing, and nomination and integration of all sensors. We work cross functionally with systems, perceptions, vehicle integration to ensure the sensors meet Latitude’s ODD requirements, perception requirements, and that it is integrable and reliable in Ford’s series vehicles. We are expected to understand sensing from a first principle approach and to ensure those principles are designable and manufacturable.  We keep a breadth of all sensing technology, sensing vendors, and integration technologies. Members of the team are expected to be highly multidisciplinary, as successful sensor integration requires expert understanding and comfortability of concepts across many disciplines–from hardware and software.

What you’ll do: 

• Lead technical development of radar or lidar sensing systems from early concept, benchmarking, and sourcing through production launch
• Define sensor performance targets, requirements, evaluation criteria, and validation plans based on vehicle, perception, and ODD needs
• Drive sensor benchmarking and technical down-selection across candidate suppliers and technologies
• Lead supplier technical engagement, including requirements reviews, data reviews, architecture discussions, issue resolution, and design maturity assessments
• Guide architecture and tradeoff decisions related to sensing performance, environmental robustness, packaging, thermal constraints, power, diagnostics, manufacturability, and cost
• Work cross-functionally with systems, perception, firmware, validation, vehicle integration, manufacturing, and quality teams to ensure the sensor meets downstream functional and program needs
• Review test data from supplier, bench, track, and vehicle testing; identify performance gaps; determine root cause; and drive corrective actions
• Assess whether supplier evidence is technically credible by reviewing test conditions, assumptions, filtering, sample quality, boundary cases, repeatability, and alignment to sensor physics and system requirements
• Lead technical reviews and challenge unsupported claims, weak correlation, incomplete validation, and conclusions that do not match observed data or first-principles behavior
• Establish technical plans, milestones, risks, and mitigation strategies to keep sensor programs on track toward nomination and launch
• Communicate technical status, open issues, and tradeoffs clearly to engineering leadership and cross-functional partners

What you'll need to succeed:

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 7+ years of relevant experience (or Master's degree and 5+ years of relevant experience, or PhD and 2+ years of relevant experience)
• 8+ years of experience in automotive sensing, with deep hands-on expertise in either radar or lidar and demonstrated technical leadership on complex hardware programs
• Strong first-principles understanding of the relevant sensing modality:
  • Radar: RF fundamentals, range/Doppler/angle estimation, resolution, interference, multipath, ghosting, calibration, synchronization, and environmental effects
  • Lidar: time-of-flight or FMCW fundamentals, ranging accuracy, reflectivity effects, point cloud quality, contamination, weather impacts, optical alignment, calibration, and environmental robustness
• Strong scripting and analysis capability in python, including hands-on use of NumPy, pandas, Jupyter, and similar tools to parse logs, evaluate sensor performance, trend issues, and build repeatable analysis workflows
• Ability to work directly with sensor data and debug artifacts, including supplier logs, raw captures, decoded outputs, and vehicle test datasets, and determine whether the data is complete, valid, and physically credible
• Practical experience with day-to-day engineering tools such as Wireshark/PCAP analysis, CAN tools (CANoe/CANalyzer or similar), ROS/rosbag or equivalent logging frameworks, point cloud or radar visualization tools, and common automotive data interfaces such as CAN, CAN FD, and automotive Ethernet
• Ability to independently judge whether supplier test results are correct by evaluating test setup, calibration state, ground truth method, statistical significance, repeatability, boundary conditions, applied filters, KPI definitions, and consistency with known sensor behavior
• Ability to lead and critically assess technical design reviews (TDRs) by identifying weak assumptions, incomplete validation, inconsistent requirements traceability, misleading metrics, and conclusions that are not supported by the underlying data
• Experience translating system and perception needs into sensor requirements, validation methods, and supplier deliverables
• Experience working across hardware, firmware, systems, perception, validation, manufacturing, and supplier teams to drive root cause and resolution
• Strong technical judgment and communication skills, with the ability to make and defend tradeoffs across performance, cost, timing, integration, and reliability

Nice to have: 

• Master’s degree or PhD in Electrical Engineering, Physics, Robotics, Computer Science, or a related field
• Experience leading supplier nomination, sourcing, or technical selection for radar or lidar hardware
• Experience bringing radar or lidar systems into automotive production
• Familiarity with DV/PV, DFMEA, APQP, PPAP, functional safety, automotive quality processes, and production release expectations
• Working knowledge of perception, tracking, calibration, and downstream use of radar or lidar data in automated driving systems
• Experience supporting multiple vehicle platforms or series-production programs

What we offer you:

• Competitive compensation packages
• High-quality individual and family medical, dental, and vision insurance
• Health savings account with available employer match
• Employer-matched 401(k) retirement plan with immediate vesting
• Employer-paid group term life insurance and the option to elect voluntary life insurance
• Paid parental leave
• Paid medical leave
• Unlimited vacation
• 15 paid holidays
• Daily lunches, snacks, and beverages available in all office locations
• Pre-tax spending accounts for healthcare and dependent care expenses
• Pre-tax commuter benefits
• Monthly wellness stipend
• Adoption/Surrogacy support program
• Backup child and elder care program
• Professional development reimbursement
• Employee assistance program
• Discounted programs that include legal services, identity theft protection, pet insurance, and more
• Company and team bonding outlets: employee resource groups, quarterly team activity stipend, and wellness initiatives

Learn more about Latitude’s team, mission and career opportunities at lat.ai!

The expected base salary range for this full-time position in California is $191,920 - $287,880 USD. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Latitude employees are also eligible to participate in Latitude’s annual bonus programs, equity compensation, and generous Company benefits program, subject to eligibility requirements.

Candidates for positions with Latitude AI must be legally authorized to work in the United States on a permanent basis. Verification of employment eligibility will be required at the time of hire. Visa sponsorship is available for this position.

We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status.

Latitude AI (lat.ai) develops automated driving technologies, including L3, for Ford vehicles at scale. We’re driven by the opportunity to reimagine what it’s like to drive and make travel safer, less stressful, and more enjoyable for everyone.

When you join the Latitude team, you’ll work alongside leading experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, systems and safety engineering – all dedicated to making a real, positive impact on the driving experience for millions of people. 

As a Ford Motor Company subsidiary, we operate independently to develop automated driving technology at the speed of a technology startup. Latitude is headquartered in Pittsburgh with engineering centers in Dearborn, Mich., and Palo Alto, Calif.

Meet the team:

The hardware sensing team is responsible for the benchmarking, characterizing, and nomination and integration of all sensors. We work cross functionally with systems, perceptions, vehicle integration to ensure the sensors meet Latitude’s ODD requirements, perception requirements, and that it is integrable and reliable in Ford’s series vehicles. We are expected to understand sensing from a first principle approach and to ensure those principles are designable and manufacturable.  We keep a breadth of all sensing technology, sensing vendors, and integration technologies. Members of the team are expected to be highly multidisciplinary, as successful sensor integration requires expert understanding and comfortability of concepts across many disciplines–from hardware and software.

What you’ll do: 

• Lead technical development of radar or lidar sensing systems from early concept, benchmarking, and sourcing through production launch
• Define sensor performance targets, requirements, evaluation criteria, and validation plans based on vehicle, perception, and ODD needs
• Drive sensor benchmarking and technical down-selection across candidate suppliers and technologies
• Lead supplier technical engagement, including requirements reviews, data reviews, architecture discussions, issue resolution, and design maturity assessments
• Guide architecture and tradeoff decisions related to sensing performance, environmental robustness, packaging, thermal constraints, power, diagnostics, manufacturability, and cost
• Work cross-functionally with systems, perception, firmware, validation, vehicle integration, manufacturing, and quality teams to ensure the sensor meets downstream functional and program needs
• Review test data from supplier, bench, track, and vehicle testing; identify performance gaps; determine root cause; and drive corrective actions
• Assess whether supplier evidence is technically credible by reviewing test conditions, assumptions, filtering, sample quality, boundary cases, repeatability, and alignment to sensor physics and system requirements
• Lead technical reviews and challenge unsupported claims, weak correlation, incomplete validation, and conclusions that do not match observed data or first-principles behavior
• Establish technical plans, milestones, risks, and mitigation strategies to keep sensor programs on track toward nomination and launch
• Communicate technical status, open issues, and tradeoffs clearly to engineering leadership and cross-functional partners

What you'll need to succeed:

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 7+ years of relevant experience (or Master's degree and 5+ years of relevant experience, or PhD and 2+ years of relevant experience)
• 8+ years of experience in automotive sensing, with deep hands-on expertise in either radar or lidar and demonstrated technical leadership on complex hardware programs
• Strong first-principles understanding of the relevant sensing modality:
  • Radar: RF fundamentals, range/Doppler/angle estimation, resolution, interference, multipath, ghosting, calibration, synchronization, and environmental effects
  • Lidar: time-of-flight or FMCW fundamentals, ranging accuracy, reflectivity effects, point cloud quality, contamination, weather impacts, optical alignment, calibration, and environmental robustness
• Strong scripting and analysis capability in python, including hands-on use of NumPy, pandas, Jupyter, and similar tools to parse logs, evaluate sensor performance, trend issues, and build repeatable analysis workflows
• Ability to work directly with sensor data and debug artifacts, including supplier logs, raw captures, decoded outputs, and vehicle test datasets, and determine whether the data is complete, valid, and physically credible
• Practical experience with day-to-day engineering tools such as Wireshark/PCAP analysis, CAN tools (CANoe/CANalyzer or similar), ROS/rosbag or equivalent logging frameworks, point cloud or radar visualization tools, and common automotive data interfaces such as CAN, CAN FD, and automotive Ethernet
• Ability to independently judge whether supplier test results are correct by evaluating test setup, calibration state, ground truth method, statistical significance, repeatability, boundary conditions, applied filters, KPI definitions, and consistency with known sensor behavior
• Ability to lead and critically assess technical design reviews (TDRs) by identifying weak assumptions, incomplete validation, inconsistent requirements traceability, misleading metrics, and conclusions that are not supported by the underlying data
• Experience translating system and perception needs into sensor requirements, validation methods, and supplier deliverables
• Experience working across hardware, firmware, systems, perception, validation, manufacturing, and supplier teams to drive root cause and resolution
• Strong technical judgment and communication skills, with the ability to make and defend tradeoffs across performance, cost, timing, integration, and reliability

Nice to have: 

• Master’s degree or PhD in Electrical Engineering, Physics, Robotics, Computer Science, or a related field
• Experience leading supplier nomination, sourcing, or technical selection for radar or lidar hardware
• Experience bringing radar or lidar systems into automotive production
• Familiarity with DV/PV, DFMEA, APQP, PPAP, functional safety, automotive quality processes, and production release expectations
• Working knowledge of perception, tracking, calibration, and downstream use of radar or lidar data in automated driving systems
• Experience supporting multiple vehicle platforms or series-production programs

What we offer you:

• Competitive compensation packages
• High-quality individual and family medical, dental, and vision insurance
• Health savings account with available employer match
• Employer-matched 401(k) retirement plan with immediate vesting
• Employer-paid group term life insurance and the option to elect voluntary life insurance
• Paid parental leave
• Paid medical leave
• Unlimited vacation
• 15 paid holidays
• Daily lunches, snacks, and beverages available in all office locations
• Pre-tax spending accounts for healthcare and dependent care expenses
• Pre-tax commuter benefits
• Monthly wellness stipend
• Adoption/Surrogacy support program
• Backup child and elder care program
• Professional development reimbursement
• Employee assistance program
• Discounted programs that include legal services, identity theft protection, pet insurance, and more
• Company and team bonding outlets: employee resource groups, quarterly team activity stipend, and wellness initiatives

Learn more about Latitude’s team, mission and career opportunities at lat.ai!

The expected base salary range for this full-time position in California is $191,920 - $287,880 USD. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Latitude employees are also eligible to participate in Latitude’s annual bonus programs, equity compensation, and generous Company benefits program, subject to eligibility requirements.

Candidates for positions with Latitude AI must be legally authorized to work in the United States on a permanent basis. Verification of employment eligibility will be required at the time of hire. Visa sponsorship is available for this position.

We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status.

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 Machine Learning Engineer on the Data Mining team, your mission is to help build the "Brain" of this engine. You will work with state-of-the-art foundation models to extract insights from Motional’s driving data, working at the intersection of large-scale representation learning and data retrieval. By building smarter mining tools and efficient data pipelines, you will accelerate the model improvement lifecycle for teams working on post-training analysis, error diagnosis, and dataset curation.

What You'll Do:

• Build and Train ML Pipelines: Develop, train, and fine-tune machine learning models for multimodal sensor data (e.g., vision, LiDAR). Focus on implementing supervised and self-supervised learning approaches to improve data search and retrieval.
• Support Model Deployment: Implement scalable data preprocessing and augmentation pipelines. Assist in applying standard optimization techniques (e.g., batch inference, quantization) to ensure models run efficiently in production environments.
• Data Mining & Analysis: Help develop embedding-based search tools and "active learning" workflows to identify critical driving scenarios.
• Monitor Production Performance: Help build and maintain dashboards to monitor model health, data drift, and system performance. Identify regressions and assist in the operational support of our data mining services.
• Learn and Apply Best Practices: Follow software engineering standards (version control, CI/CD, unit testing) for ML code. Participate in code reviews and contribute to technical documentation.
• Collaborate Across Teams: Work closely with senior engineers and machine learning engineers to translate model prototypes into maintainable, scalable engineering solutions.
  
  

What We're Looking For (Must-Haves):

• BS or MS in Computer Science, Machine Learning, or a related field.
• Hands-on experience with PyTorch (preferred) or TensorFlow/JAX. You should be comfortable training models and evaluating them using standard metrics.
• Strong proficiency in Python with the ability to write clean, modular, and well-documented code.
• Working knowledge of version control, unit testing, and basic software design patterns.
• Experience working with large datasets, including proficiency in SQL and data libraries like Pandas and NumPy.
• A solid grasp of the full ML lifecycle, from data cleaning and feature engineering to validation and deployment basics.
• A proactive learner who thrives on constructive feedback and is eager to grow within a high-stakes engineering environment.
  
  

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.
• Publication in top-tier conferences (e.g., ICCV, CVPR, ECCV)
  
  

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.

Latitude AI (lat.ai) develops automated driving technologies, including L3, for Ford vehicles at scale. We’re driven by the opportunity to reimagine what it’s like to drive and make travel safer, less stressful, and more enjoyable for everyone.

When you join the Latitude team, you’ll work alongside leading experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, systems and safety engineering – all dedicated to making a real, positive impact on the driving experience for millions of people. 

As a Ford Motor Company subsidiary, we operate independently to develop automated driving technology at the speed of a technology startup. Latitude is headquartered in Pittsburgh with engineering centers in Dearborn, Mich., and Palo Alto, Calif.

Meet the team:

The Performance Prediction team builds the Machine Learning models, evaluation pipelines, and internal tools that help us understand how autonomy behavior changes across software releases. We work on problems that span behavior classification, ride quality detection, probabilistic trajectory prediction, and release regression analysis.

Our systems support both classical and modern ML approaches. That includes compact learned classifiers such as tree-based models for behavior and ride quality detection, as well as deep learning-based probabilistic prediction models for more complex autonomy tasks. We also build the software around those models: dataset definition, feature generation, training and tuning workflows, offline metrics, experiment tracking, and tools that help engineers inspect regressions at the slice and scenario level.

This role is a strong fit for someone who enjoys building reliable Python systems and applying rigorous ML evaluation methods in a safety-critical domain. In practice, the work is a mix of ML systems development, model and evaluation work, and internal tooling used by partner teams across autonomy.

What you’ll do: 

• Build production software for model training, offline evaluation, and release-comparison workflows
• Develop and improve learned models for performance prediction, including behavior classifiers and probabilistic prediction models
• Design training, validation, and holdout strategies that produce trustworthy results
• Define and track model and release metrics such as precision, recall, F1, ROC AUC, calibration quality, and task-specific forecasting metrics
• Run experiments, tune models, and analyze results with strong statistical rigor
• Build internal tools that help engineers compare software versions, inspect model outputs, and investigate regressions
• Partner with autonomy, simulation, and infrastructure teams to move ideas from prototype to production
• Raise engineering quality through testing, code review, CI, and maintainable interfaces across data, modeling, and product layers

What you'll need to succeed:

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 4+ years of relevant experience (or Master's degree and 2+ years of relevant experience, or PhD)
• Strong software engineering skills in Python, including experience building modular, maintainable, well-tested systems in a shared codebase
• Experience developing, training, tuning, or productionizing supervised ML models
• Strong grounding in statistics and experimental design, including experience designing model training and evaluation tests
• Experience selecting and interpreting model metrics, thresholds, and tradeoffs for real-world decision-making
• Experience with ML tooling such as PyTorch, scikit-learn, or similar frameworks
• Experience working with large datasets using SQL, pandas, and NumPy
• Strong communication skills and the ability to work effectively across software, ML, and autonomy teams

Nice to have: 

• PhD in Computer Science, Machine Learning, Statistics, Robotics, or a closely related field is preferred
• Equivalent research-heavy industry experience is highly valued
• Experience with probabilistic forecasting, trajectory prediction, sequential modeling, or graph-based models
• Experience with classical ML methods such as random forests, gradient boosting, or calibrated linear models
• Experience with calibration, uncertainty estimation, ablation studies, error analysis, or release regression methodology
• Experience building internal analytics or ML tools with Dash, Plotly, Streamlit, or similar frameworks
• Experience with workflow orchestration or experimentation tools such as Dagster, Airflow, or Weights and Biases
• Experience with Bazel or other large-scale build systems
• Prior autonomous driving experience is helpful but not required. Strong experience with production ML systems and rigorous model evaluation is sufficient

What we offer you:

• Competitive compensation packages
• High-quality individual and family medical, dental, and vision insurance
• Health savings account with available employer match
• Employer-matched 401(k) retirement plan with immediate vesting
• Employer-paid group term life insurance and the option to elect voluntary life insurance
• Paid parental leave
• Paid medical leave
• Unlimited vacation
• 15 paid holidays
• Daily lunches, snacks, and beverages available in all office locations
• Pre-tax spending accounts for healthcare and dependent care expenses
• Pre-tax commuter benefits
• Monthly wellness stipend
• Adoption/Surrogacy support program
• Backup child and elder care program
• Professional development reimbursement
• Employee assistance program
• Discounted programs that include legal services, identity theft protection, pet insurance, and more
• Company and team bonding outlets: employee resource groups, quarterly team activity stipend, and wellness initiatives

Learn more about Latitude’s team, mission and career opportunities at lat.ai!

The expected base salary range for this full-time position in California is $179,200 - $268,800 USD. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Latitude employees are also eligible to participate in Latitude’s annual bonus programs, equity compensation, and generous Company benefits program, subject to eligibility requirements.

Candidates for positions with Latitude AI must be legally authorized to work in the United States on a permanent basis. Verification of employment eligibility will be required at the time of hire. Visa sponsorship is available for this position.

We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status.

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