Senior Software Engineer - Performance Prediction

<p><span style="font-weight: 300; font-family: arial, helvetica, sans-serif;"><span style="font-weight: 400;">Latitude AI (</span><a href="https://lat.ai/"><span style="font-weight: 400;">lat.ai</span></a><span style="font-weight: 400;">) 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.</span></span></p> <p><span style="font-family: arial, helvetica, sans-serif;"><span style="font-weight: 300;">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 – </span><strong><em>all dedicated to making a real, positive impact on the driving experience for millions of people.&nbsp;</em></strong></span></p> <p><span style="font-weight: 300; font-family: arial, helvetica, sans-serif;">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.</span></p> <p><span style="font-family: arial, helvetica, sans-serif;"><strong>Meet the team:</strong></span></p> <p>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.</p> <p>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.</p> <p>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.</p> <p><span style="font-family: arial, helvetica, sans-serif;"><strong>What you’ll do:&nbsp;</strong></span></p> <ul> <li>Build production software for model training, offline evaluation, and release-comparison workflows</li> <li>Develop and improve learned models for performance prediction, including behavior classifiers and probabilistic prediction models</li> <li>Design training, validation, and holdout strategies that produce trustworthy results</li> <li>Define and track model and release metrics such as precision, recall, F1, ROC AUC, calibration quality, and task-specific forecasting metrics</li> <li>Run experiments, tune models, and analyze results with strong statistical rigor</li> <li>Build internal tools that help engineers compare software versions, inspect model outputs, and investigate regressions</li> <li>Partner with autonomy, simulation, and infrastructure teams to move ideas from prototype to production</li> <li>Raise engineering quality through testing, code review, CI, and maintainable interfaces across data, modeling, and product layers</li> </ul> <p><span style="font-family: arial, helvetica, sans-serif;"><strong>What you'll need to succeed:</strong></span></p> <ul> <li>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)</li> <li>Strong software engineering skills in Python, including experience building modular, maintainable, well-tested systems in a shared codebase</li> <li>Experience developing, training, tuning, or productionizing supervised ML models</li> <li>Strong grounding in statistics and experimental design, including experience designing model training and evaluation tests</li> <li>Experience selecting and interpreting model metrics, thresholds, and tradeoffs for real-world decision-making</li> <li>Experience with ML tooling such as PyTorch, scikit-learn, or similar frameworks</li> <li>Experience working with large datasets using SQL, pandas, and NumPy</li> <li>Strong communication skills and the ability to work effectively across software, ML, and autonomy teams</li> </ul> <p><span style="font-family: arial, helvetica, sans-serif;"><strong>Nice to have:</strong><span style="font-weight: 300;">&nbsp;</span></span></p> <ul> <li>PhD in Computer Science, Machine Learning, Statistics, Robotics, or a closely related field is preferred</li> <li>Equivalent research-heavy industry experience is highly valued</li> <li>Experience with probabilistic forecasting, trajectory prediction, sequential modeling, or graph-based models</li> <li>Experience with classical ML methods such as random forests, gradient boosting, or calibrated linear models</li> <li>Experience with calibration, uncertainty estimation, ablation studies, error analysis, or release regression methodology</li> <li>Experience building internal analytics or ML tools with Dash, Plotly, Streamlit, or similar frameworks</li> <li>Experience with workflow orchestration or experimentation tools such as Dagster, Airflow, or Weights and Biases</li> <li>Experience with Bazel or other large-scale build systems</li> <li>Prior autonomous driving experience is helpful but not required. Strong experience with production ML systems and rigorous model evaluation is sufficient</li> </ul> <p><span style="font-family: arial, helvetica, sans-serif;"><strong>What we offer you:</strong></span></p> <ul> <li style="font-weight: 300;"><span style="font-weight: 300; font-family: arial, helvetica, sans-serif;">Competitive compensation packages</span></li> <li style="font-weight: 300;"><span style="font-weight: 300; font-family: arial, helvetica, sans-serif;">High-quality individual and family medical, dental, and vision insurance</span></li> <li style="font-weight: 300;"><span style="font-weight: 300; font-family: arial, helvetica, sans-serif;">Health savings account with available employer match</span></li> <li style="font-weight: 300;"><span style="font-weight: 300; font-family: arial, helvetica, sans-serif;">Employer-matched 401(k) retirement plan with immediate vesting</span></li> <li style="font-weight: 300;"><span style="font-weight: 300; font-family: arial, helvetica, sans-serif;">Employer-paid group term life insurance and the option to elect voluntary life insurance</span></li> <li style="font-weight: 300;"><span style="font-weight: 300; font-family: arial, helvetica, sans-serif;">Paid parental leave</span></li> <li style="font-weight: 300;"><span style="font-weight: 300; font-family: arial, helvetica, sans-serif;">Paid medical leave</span></li> <li style="font-weight: 300;"><span style="font-weight: 300; font-family: arial, helvetica, sans-serif;">Unlimited vacation</span></li> <li style="font-weight: 300;"><span style="font-weight: 300; font-family: arial, helvetica, sans-serif;">15 paid holidays</span></li> <li>Daily lunches, snacks, and beverages available in all office locations</li> <li style="font-weight: 300;"><span style="font-weight: 300; font-family: arial, helvetica, sans-serif;">Pre-tax spending accounts for healthcare and dependent care expenses</span></li> <li style="font-weight: 300;"><span style="font-weight: 300; font-family: arial, helvetica, sans-serif;">Pre-tax commuter benefits</span></li> <li style="font-weight: 300;"><span style="font-weight: 300; font-family: arial, helvetica, sans-serif;">Monthly wellness stipend</span></li> <li style="font-weight: 300;"><span style="font-weight: 300; font-family: arial, helvetica, sans-serif;">Adoption/Surrogacy support program</span></li> <li style="font-weight: 300;"><span style="font-weight: 300; font-family: arial, helvetica, sans-serif;">Backup child and elder care program</span></li> <li style="font-weight: 300;"><span style="font-weight: 300; font-family: arial, helvetica, sans-serif;">Professional development reimbursement</span></li> <li style="font-weight: 300;"><span style="font-weight: 300; font-family: arial, helvetica, sans-serif;">Employee assistance program</span></li> <li style="font-weight: 300;"><span style="font-weight: 300; font-family: arial, helvetica, sans-serif;">Discounted programs that include legal services, identity theft protection, pet insurance, and more</span></li> <li style="font-weight: 300;"><span style="font-weight: 300; font-family: arial, helvetica, sans-serif;">Company and team bonding outlets: employee resource groups, quarterly team activity stipend, and wellness initiatives</span></li> </ul> <p><span style="font-weight: 300; font-family: arial, helvetica, sans-serif;"><span style="font-weight: 400;">Learn more about Latitude’s team, mission and career opportunities at </span><a href="https://lat.ai/"><span style="font-weight: 400;">lat.ai</span></a><span style="font-weight: 400;">!</span></span></p> <p><span style="font-weight: 300; font-family: arial, helvetica, sans-serif;"><span style="font-weight: 400;">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.</span></span></p> <p>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.</p> <p>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.</p> <p>&nbsp;</p> <p><span style="font-weight: 300; font-family: arial, helvetica, sans-serif;"><span style="color: rgb(255, 255, 255);"><strong>#LI-CQ1</strong></span></span></p>